Source file src/google.golang.org/genproto/googleapis/cloud/bigquery/v2/model.pb.go

Documentation: google.golang.org/genproto/googleapis/cloud/bigquery/v2

     1  // Copyright 2021 Google LLC
     2  //
     3  // Licensed under the Apache License, Version 2.0 (the "License");
     4  // you may not use this file except in compliance with the License.
     5  // You may obtain a copy of the License at
     6  //
     7  //     http://www.apache.org/licenses/LICENSE-2.0
     8  //
     9  // Unless required by applicable law or agreed to in writing, software
    10  // distributed under the License is distributed on an "AS IS" BASIS,
    11  // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    12  // See the License for the specific language governing permissions and
    13  // limitations under the License.
    14  
    15  // Code generated by protoc-gen-go. DO NOT EDIT.
    16  // versions:
    17  // 	protoc-gen-go v1.26.0
    18  // 	protoc        v3.12.2
    19  // source: google/cloud/bigquery/v2/model.proto
    20  
    21  package bigquery
    22  
    23  import (
    24  	context "context"
    25  	reflect "reflect"
    26  	sync "sync"
    27  
    28  	_ "google.golang.org/genproto/googleapis/api/annotations"
    29  	grpc "google.golang.org/grpc"
    30  	codes "google.golang.org/grpc/codes"
    31  	status "google.golang.org/grpc/status"
    32  	protoreflect "google.golang.org/protobuf/reflect/protoreflect"
    33  	protoimpl "google.golang.org/protobuf/runtime/protoimpl"
    34  	emptypb "google.golang.org/protobuf/types/known/emptypb"
    35  	timestamppb "google.golang.org/protobuf/types/known/timestamppb"
    36  	wrapperspb "google.golang.org/protobuf/types/known/wrapperspb"
    37  )
    38  
    39  const (
    40  	// Verify that this generated code is sufficiently up-to-date.
    41  	_ = protoimpl.EnforceVersion(20 - protoimpl.MinVersion)
    42  	// Verify that runtime/protoimpl is sufficiently up-to-date.
    43  	_ = protoimpl.EnforceVersion(protoimpl.MaxVersion - 20)
    44  )
    45  
    46  // Indicates the type of the Model.
    47  type Model_ModelType int32
    48  
    49  const (
    50  	Model_MODEL_TYPE_UNSPECIFIED Model_ModelType = 0
    51  	// Linear regression model.
    52  	Model_LINEAR_REGRESSION Model_ModelType = 1
    53  	// Logistic regression based classification model.
    54  	Model_LOGISTIC_REGRESSION Model_ModelType = 2
    55  	// K-means clustering model.
    56  	Model_KMEANS Model_ModelType = 3
    57  	// Matrix factorization model.
    58  	Model_MATRIX_FACTORIZATION Model_ModelType = 4
    59  	// DNN classifier model.
    60  	Model_DNN_CLASSIFIER Model_ModelType = 5
    61  	// An imported TensorFlow model.
    62  	Model_TENSORFLOW Model_ModelType = 6
    63  	// DNN regressor model.
    64  	Model_DNN_REGRESSOR Model_ModelType = 7
    65  	// Boosted tree regressor model.
    66  	Model_BOOSTED_TREE_REGRESSOR Model_ModelType = 9
    67  	// Boosted tree classifier model.
    68  	Model_BOOSTED_TREE_CLASSIFIER Model_ModelType = 10
    69  	// ARIMA model.
    70  	Model_ARIMA Model_ModelType = 11
    71  	// [Beta] AutoML Tables regression model.
    72  	Model_AUTOML_REGRESSOR Model_ModelType = 12
    73  	// [Beta] AutoML Tables classification model.
    74  	Model_AUTOML_CLASSIFIER Model_ModelType = 13
    75  	// New name for the ARIMA model.
    76  	Model_ARIMA_PLUS Model_ModelType = 19
    77  )
    78  
    79  // Enum value maps for Model_ModelType.
    80  var (
    81  	Model_ModelType_name = map[int32]string{
    82  		0:  "MODEL_TYPE_UNSPECIFIED",
    83  		1:  "LINEAR_REGRESSION",
    84  		2:  "LOGISTIC_REGRESSION",
    85  		3:  "KMEANS",
    86  		4:  "MATRIX_FACTORIZATION",
    87  		5:  "DNN_CLASSIFIER",
    88  		6:  "TENSORFLOW",
    89  		7:  "DNN_REGRESSOR",
    90  		9:  "BOOSTED_TREE_REGRESSOR",
    91  		10: "BOOSTED_TREE_CLASSIFIER",
    92  		11: "ARIMA",
    93  		12: "AUTOML_REGRESSOR",
    94  		13: "AUTOML_CLASSIFIER",
    95  		19: "ARIMA_PLUS",
    96  	}
    97  	Model_ModelType_value = map[string]int32{
    98  		"MODEL_TYPE_UNSPECIFIED":  0,
    99  		"LINEAR_REGRESSION":       1,
   100  		"LOGISTIC_REGRESSION":     2,
   101  		"KMEANS":                  3,
   102  		"MATRIX_FACTORIZATION":    4,
   103  		"DNN_CLASSIFIER":          5,
   104  		"TENSORFLOW":              6,
   105  		"DNN_REGRESSOR":           7,
   106  		"BOOSTED_TREE_REGRESSOR":  9,
   107  		"BOOSTED_TREE_CLASSIFIER": 10,
   108  		"ARIMA":                   11,
   109  		"AUTOML_REGRESSOR":        12,
   110  		"AUTOML_CLASSIFIER":       13,
   111  		"ARIMA_PLUS":              19,
   112  	}
   113  )
   114  
   115  func (x Model_ModelType) Enum() *Model_ModelType {
   116  	p := new(Model_ModelType)
   117  	*p = x
   118  	return p
   119  }
   120  
   121  func (x Model_ModelType) String() string {
   122  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   123  }
   124  
   125  func (Model_ModelType) Descriptor() protoreflect.EnumDescriptor {
   126  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[0].Descriptor()
   127  }
   128  
   129  func (Model_ModelType) Type() protoreflect.EnumType {
   130  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[0]
   131  }
   132  
   133  func (x Model_ModelType) Number() protoreflect.EnumNumber {
   134  	return protoreflect.EnumNumber(x)
   135  }
   136  
   137  // Deprecated: Use Model_ModelType.Descriptor instead.
   138  func (Model_ModelType) EnumDescriptor() ([]byte, []int) {
   139  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 0}
   140  }
   141  
   142  // Loss metric to evaluate model training performance.
   143  type Model_LossType int32
   144  
   145  const (
   146  	Model_LOSS_TYPE_UNSPECIFIED Model_LossType = 0
   147  	// Mean squared loss, used for linear regression.
   148  	Model_MEAN_SQUARED_LOSS Model_LossType = 1
   149  	// Mean log loss, used for logistic regression.
   150  	Model_MEAN_LOG_LOSS Model_LossType = 2
   151  )
   152  
   153  // Enum value maps for Model_LossType.
   154  var (
   155  	Model_LossType_name = map[int32]string{
   156  		0: "LOSS_TYPE_UNSPECIFIED",
   157  		1: "MEAN_SQUARED_LOSS",
   158  		2: "MEAN_LOG_LOSS",
   159  	}
   160  	Model_LossType_value = map[string]int32{
   161  		"LOSS_TYPE_UNSPECIFIED": 0,
   162  		"MEAN_SQUARED_LOSS":     1,
   163  		"MEAN_LOG_LOSS":         2,
   164  	}
   165  )
   166  
   167  func (x Model_LossType) Enum() *Model_LossType {
   168  	p := new(Model_LossType)
   169  	*p = x
   170  	return p
   171  }
   172  
   173  func (x Model_LossType) String() string {
   174  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   175  }
   176  
   177  func (Model_LossType) Descriptor() protoreflect.EnumDescriptor {
   178  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[1].Descriptor()
   179  }
   180  
   181  func (Model_LossType) Type() protoreflect.EnumType {
   182  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[1]
   183  }
   184  
   185  func (x Model_LossType) Number() protoreflect.EnumNumber {
   186  	return protoreflect.EnumNumber(x)
   187  }
   188  
   189  // Deprecated: Use Model_LossType.Descriptor instead.
   190  func (Model_LossType) EnumDescriptor() ([]byte, []int) {
   191  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 1}
   192  }
   193  
   194  // Distance metric used to compute the distance between two points.
   195  type Model_DistanceType int32
   196  
   197  const (
   198  	Model_DISTANCE_TYPE_UNSPECIFIED Model_DistanceType = 0
   199  	// Eculidean distance.
   200  	Model_EUCLIDEAN Model_DistanceType = 1
   201  	// Cosine distance.
   202  	Model_COSINE Model_DistanceType = 2
   203  )
   204  
   205  // Enum value maps for Model_DistanceType.
   206  var (
   207  	Model_DistanceType_name = map[int32]string{
   208  		0: "DISTANCE_TYPE_UNSPECIFIED",
   209  		1: "EUCLIDEAN",
   210  		2: "COSINE",
   211  	}
   212  	Model_DistanceType_value = map[string]int32{
   213  		"DISTANCE_TYPE_UNSPECIFIED": 0,
   214  		"EUCLIDEAN":                 1,
   215  		"COSINE":                    2,
   216  	}
   217  )
   218  
   219  func (x Model_DistanceType) Enum() *Model_DistanceType {
   220  	p := new(Model_DistanceType)
   221  	*p = x
   222  	return p
   223  }
   224  
   225  func (x Model_DistanceType) String() string {
   226  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   227  }
   228  
   229  func (Model_DistanceType) Descriptor() protoreflect.EnumDescriptor {
   230  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[2].Descriptor()
   231  }
   232  
   233  func (Model_DistanceType) Type() protoreflect.EnumType {
   234  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[2]
   235  }
   236  
   237  func (x Model_DistanceType) Number() protoreflect.EnumNumber {
   238  	return protoreflect.EnumNumber(x)
   239  }
   240  
   241  // Deprecated: Use Model_DistanceType.Descriptor instead.
   242  func (Model_DistanceType) EnumDescriptor() ([]byte, []int) {
   243  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 2}
   244  }
   245  
   246  // Indicates the method to split input data into multiple tables.
   247  type Model_DataSplitMethod int32
   248  
   249  const (
   250  	Model_DATA_SPLIT_METHOD_UNSPECIFIED Model_DataSplitMethod = 0
   251  	// Splits data randomly.
   252  	Model_RANDOM Model_DataSplitMethod = 1
   253  	// Splits data with the user provided tags.
   254  	Model_CUSTOM Model_DataSplitMethod = 2
   255  	// Splits data sequentially.
   256  	Model_SEQUENTIAL Model_DataSplitMethod = 3
   257  	// Data split will be skipped.
   258  	Model_NO_SPLIT Model_DataSplitMethod = 4
   259  	// Splits data automatically: Uses NO_SPLIT if the data size is small.
   260  	// Otherwise uses RANDOM.
   261  	Model_AUTO_SPLIT Model_DataSplitMethod = 5
   262  )
   263  
   264  // Enum value maps for Model_DataSplitMethod.
   265  var (
   266  	Model_DataSplitMethod_name = map[int32]string{
   267  		0: "DATA_SPLIT_METHOD_UNSPECIFIED",
   268  		1: "RANDOM",
   269  		2: "CUSTOM",
   270  		3: "SEQUENTIAL",
   271  		4: "NO_SPLIT",
   272  		5: "AUTO_SPLIT",
   273  	}
   274  	Model_DataSplitMethod_value = map[string]int32{
   275  		"DATA_SPLIT_METHOD_UNSPECIFIED": 0,
   276  		"RANDOM":                        1,
   277  		"CUSTOM":                        2,
   278  		"SEQUENTIAL":                    3,
   279  		"NO_SPLIT":                      4,
   280  		"AUTO_SPLIT":                    5,
   281  	}
   282  )
   283  
   284  func (x Model_DataSplitMethod) Enum() *Model_DataSplitMethod {
   285  	p := new(Model_DataSplitMethod)
   286  	*p = x
   287  	return p
   288  }
   289  
   290  func (x Model_DataSplitMethod) String() string {
   291  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   292  }
   293  
   294  func (Model_DataSplitMethod) Descriptor() protoreflect.EnumDescriptor {
   295  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[3].Descriptor()
   296  }
   297  
   298  func (Model_DataSplitMethod) Type() protoreflect.EnumType {
   299  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[3]
   300  }
   301  
   302  func (x Model_DataSplitMethod) Number() protoreflect.EnumNumber {
   303  	return protoreflect.EnumNumber(x)
   304  }
   305  
   306  // Deprecated: Use Model_DataSplitMethod.Descriptor instead.
   307  func (Model_DataSplitMethod) EnumDescriptor() ([]byte, []int) {
   308  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 3}
   309  }
   310  
   311  // Type of supported data frequency for time series forecasting models.
   312  type Model_DataFrequency int32
   313  
   314  const (
   315  	Model_DATA_FREQUENCY_UNSPECIFIED Model_DataFrequency = 0
   316  	// Automatically inferred from timestamps.
   317  	Model_AUTO_FREQUENCY Model_DataFrequency = 1
   318  	// Yearly data.
   319  	Model_YEARLY Model_DataFrequency = 2
   320  	// Quarterly data.
   321  	Model_QUARTERLY Model_DataFrequency = 3
   322  	// Monthly data.
   323  	Model_MONTHLY Model_DataFrequency = 4
   324  	// Weekly data.
   325  	Model_WEEKLY Model_DataFrequency = 5
   326  	// Daily data.
   327  	Model_DAILY Model_DataFrequency = 6
   328  	// Hourly data.
   329  	Model_HOURLY Model_DataFrequency = 7
   330  	// Per-minute data.
   331  	Model_PER_MINUTE Model_DataFrequency = 8
   332  )
   333  
   334  // Enum value maps for Model_DataFrequency.
   335  var (
   336  	Model_DataFrequency_name = map[int32]string{
   337  		0: "DATA_FREQUENCY_UNSPECIFIED",
   338  		1: "AUTO_FREQUENCY",
   339  		2: "YEARLY",
   340  		3: "QUARTERLY",
   341  		4: "MONTHLY",
   342  		5: "WEEKLY",
   343  		6: "DAILY",
   344  		7: "HOURLY",
   345  		8: "PER_MINUTE",
   346  	}
   347  	Model_DataFrequency_value = map[string]int32{
   348  		"DATA_FREQUENCY_UNSPECIFIED": 0,
   349  		"AUTO_FREQUENCY":             1,
   350  		"YEARLY":                     2,
   351  		"QUARTERLY":                  3,
   352  		"MONTHLY":                    4,
   353  		"WEEKLY":                     5,
   354  		"DAILY":                      6,
   355  		"HOURLY":                     7,
   356  		"PER_MINUTE":                 8,
   357  	}
   358  )
   359  
   360  func (x Model_DataFrequency) Enum() *Model_DataFrequency {
   361  	p := new(Model_DataFrequency)
   362  	*p = x
   363  	return p
   364  }
   365  
   366  func (x Model_DataFrequency) String() string {
   367  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   368  }
   369  
   370  func (Model_DataFrequency) Descriptor() protoreflect.EnumDescriptor {
   371  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[4].Descriptor()
   372  }
   373  
   374  func (Model_DataFrequency) Type() protoreflect.EnumType {
   375  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[4]
   376  }
   377  
   378  func (x Model_DataFrequency) Number() protoreflect.EnumNumber {
   379  	return protoreflect.EnumNumber(x)
   380  }
   381  
   382  // Deprecated: Use Model_DataFrequency.Descriptor instead.
   383  func (Model_DataFrequency) EnumDescriptor() ([]byte, []int) {
   384  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 4}
   385  }
   386  
   387  // Type of supported holiday regions for time series forecasting models.
   388  type Model_HolidayRegion int32
   389  
   390  const (
   391  	// Holiday region unspecified.
   392  	Model_HOLIDAY_REGION_UNSPECIFIED Model_HolidayRegion = 0
   393  	// Global.
   394  	Model_GLOBAL Model_HolidayRegion = 1
   395  	// North America.
   396  	Model_NA Model_HolidayRegion = 2
   397  	// Japan and Asia Pacific: Korea, Greater China, India, Australia, and New
   398  	// Zealand.
   399  	Model_JAPAC Model_HolidayRegion = 3
   400  	// Europe, the Middle East and Africa.
   401  	Model_EMEA Model_HolidayRegion = 4
   402  	// Latin America and the Caribbean.
   403  	Model_LAC Model_HolidayRegion = 5
   404  	// United Arab Emirates
   405  	Model_AE Model_HolidayRegion = 6
   406  	// Argentina
   407  	Model_AR Model_HolidayRegion = 7
   408  	// Austria
   409  	Model_AT Model_HolidayRegion = 8
   410  	// Australia
   411  	Model_AU Model_HolidayRegion = 9
   412  	// Belgium
   413  	Model_BE Model_HolidayRegion = 10
   414  	// Brazil
   415  	Model_BR Model_HolidayRegion = 11
   416  	// Canada
   417  	Model_CA Model_HolidayRegion = 12
   418  	// Switzerland
   419  	Model_CH Model_HolidayRegion = 13
   420  	// Chile
   421  	Model_CL Model_HolidayRegion = 14
   422  	// China
   423  	Model_CN Model_HolidayRegion = 15
   424  	// Colombia
   425  	Model_CO Model_HolidayRegion = 16
   426  	// Czechoslovakia
   427  	Model_CS Model_HolidayRegion = 17
   428  	// Czech Republic
   429  	Model_CZ Model_HolidayRegion = 18
   430  	// Germany
   431  	Model_DE Model_HolidayRegion = 19
   432  	// Denmark
   433  	Model_DK Model_HolidayRegion = 20
   434  	// Algeria
   435  	Model_DZ Model_HolidayRegion = 21
   436  	// Ecuador
   437  	Model_EC Model_HolidayRegion = 22
   438  	// Estonia
   439  	Model_EE Model_HolidayRegion = 23
   440  	// Egypt
   441  	Model_EG Model_HolidayRegion = 24
   442  	// Spain
   443  	Model_ES Model_HolidayRegion = 25
   444  	// Finland
   445  	Model_FI Model_HolidayRegion = 26
   446  	// France
   447  	Model_FR Model_HolidayRegion = 27
   448  	// Great Britain (United Kingdom)
   449  	Model_GB Model_HolidayRegion = 28
   450  	// Greece
   451  	Model_GR Model_HolidayRegion = 29
   452  	// Hong Kong
   453  	Model_HK Model_HolidayRegion = 30
   454  	// Hungary
   455  	Model_HU Model_HolidayRegion = 31
   456  	// Indonesia
   457  	Model_ID Model_HolidayRegion = 32
   458  	// Ireland
   459  	Model_IE Model_HolidayRegion = 33
   460  	// Israel
   461  	Model_IL Model_HolidayRegion = 34
   462  	// India
   463  	Model_IN Model_HolidayRegion = 35
   464  	// Iran
   465  	Model_IR Model_HolidayRegion = 36
   466  	// Italy
   467  	Model_IT Model_HolidayRegion = 37
   468  	// Japan
   469  	Model_JP Model_HolidayRegion = 38
   470  	// Korea (South)
   471  	Model_KR Model_HolidayRegion = 39
   472  	// Latvia
   473  	Model_LV Model_HolidayRegion = 40
   474  	// Morocco
   475  	Model_MA Model_HolidayRegion = 41
   476  	// Mexico
   477  	Model_MX Model_HolidayRegion = 42
   478  	// Malaysia
   479  	Model_MY Model_HolidayRegion = 43
   480  	// Nigeria
   481  	Model_NG Model_HolidayRegion = 44
   482  	// Netherlands
   483  	Model_NL Model_HolidayRegion = 45
   484  	// Norway
   485  	Model_NO Model_HolidayRegion = 46
   486  	// New Zealand
   487  	Model_NZ Model_HolidayRegion = 47
   488  	// Peru
   489  	Model_PE Model_HolidayRegion = 48
   490  	// Philippines
   491  	Model_PH Model_HolidayRegion = 49
   492  	// Pakistan
   493  	Model_PK Model_HolidayRegion = 50
   494  	// Poland
   495  	Model_PL Model_HolidayRegion = 51
   496  	// Portugal
   497  	Model_PT Model_HolidayRegion = 52
   498  	// Romania
   499  	Model_RO Model_HolidayRegion = 53
   500  	// Serbia
   501  	Model_RS Model_HolidayRegion = 54
   502  	// Russian Federation
   503  	Model_RU Model_HolidayRegion = 55
   504  	// Saudi Arabia
   505  	Model_SA Model_HolidayRegion = 56
   506  	// Sweden
   507  	Model_SE Model_HolidayRegion = 57
   508  	// Singapore
   509  	Model_SG Model_HolidayRegion = 58
   510  	// Slovenia
   511  	Model_SI Model_HolidayRegion = 59
   512  	// Slovakia
   513  	Model_SK Model_HolidayRegion = 60
   514  	// Thailand
   515  	Model_TH Model_HolidayRegion = 61
   516  	// Turkey
   517  	Model_TR Model_HolidayRegion = 62
   518  	// Taiwan
   519  	Model_TW Model_HolidayRegion = 63
   520  	// Ukraine
   521  	Model_UA Model_HolidayRegion = 64
   522  	// United States
   523  	Model_US Model_HolidayRegion = 65
   524  	// Venezuela
   525  	Model_VE Model_HolidayRegion = 66
   526  	// Viet Nam
   527  	Model_VN Model_HolidayRegion = 67
   528  	// South Africa
   529  	Model_ZA Model_HolidayRegion = 68
   530  )
   531  
   532  // Enum value maps for Model_HolidayRegion.
   533  var (
   534  	Model_HolidayRegion_name = map[int32]string{
   535  		0:  "HOLIDAY_REGION_UNSPECIFIED",
   536  		1:  "GLOBAL",
   537  		2:  "NA",
   538  		3:  "JAPAC",
   539  		4:  "EMEA",
   540  		5:  "LAC",
   541  		6:  "AE",
   542  		7:  "AR",
   543  		8:  "AT",
   544  		9:  "AU",
   545  		10: "BE",
   546  		11: "BR",
   547  		12: "CA",
   548  		13: "CH",
   549  		14: "CL",
   550  		15: "CN",
   551  		16: "CO",
   552  		17: "CS",
   553  		18: "CZ",
   554  		19: "DE",
   555  		20: "DK",
   556  		21: "DZ",
   557  		22: "EC",
   558  		23: "EE",
   559  		24: "EG",
   560  		25: "ES",
   561  		26: "FI",
   562  		27: "FR",
   563  		28: "GB",
   564  		29: "GR",
   565  		30: "HK",
   566  		31: "HU",
   567  		32: "ID",
   568  		33: "IE",
   569  		34: "IL",
   570  		35: "IN",
   571  		36: "IR",
   572  		37: "IT",
   573  		38: "JP",
   574  		39: "KR",
   575  		40: "LV",
   576  		41: "MA",
   577  		42: "MX",
   578  		43: "MY",
   579  		44: "NG",
   580  		45: "NL",
   581  		46: "NO",
   582  		47: "NZ",
   583  		48: "PE",
   584  		49: "PH",
   585  		50: "PK",
   586  		51: "PL",
   587  		52: "PT",
   588  		53: "RO",
   589  		54: "RS",
   590  		55: "RU",
   591  		56: "SA",
   592  		57: "SE",
   593  		58: "SG",
   594  		59: "SI",
   595  		60: "SK",
   596  		61: "TH",
   597  		62: "TR",
   598  		63: "TW",
   599  		64: "UA",
   600  		65: "US",
   601  		66: "VE",
   602  		67: "VN",
   603  		68: "ZA",
   604  	}
   605  	Model_HolidayRegion_value = map[string]int32{
   606  		"HOLIDAY_REGION_UNSPECIFIED": 0,
   607  		"GLOBAL":                     1,
   608  		"NA":                         2,
   609  		"JAPAC":                      3,
   610  		"EMEA":                       4,
   611  		"LAC":                        5,
   612  		"AE":                         6,
   613  		"AR":                         7,
   614  		"AT":                         8,
   615  		"AU":                         9,
   616  		"BE":                         10,
   617  		"BR":                         11,
   618  		"CA":                         12,
   619  		"CH":                         13,
   620  		"CL":                         14,
   621  		"CN":                         15,
   622  		"CO":                         16,
   623  		"CS":                         17,
   624  		"CZ":                         18,
   625  		"DE":                         19,
   626  		"DK":                         20,
   627  		"DZ":                         21,
   628  		"EC":                         22,
   629  		"EE":                         23,
   630  		"EG":                         24,
   631  		"ES":                         25,
   632  		"FI":                         26,
   633  		"FR":                         27,
   634  		"GB":                         28,
   635  		"GR":                         29,
   636  		"HK":                         30,
   637  		"HU":                         31,
   638  		"ID":                         32,
   639  		"IE":                         33,
   640  		"IL":                         34,
   641  		"IN":                         35,
   642  		"IR":                         36,
   643  		"IT":                         37,
   644  		"JP":                         38,
   645  		"KR":                         39,
   646  		"LV":                         40,
   647  		"MA":                         41,
   648  		"MX":                         42,
   649  		"MY":                         43,
   650  		"NG":                         44,
   651  		"NL":                         45,
   652  		"NO":                         46,
   653  		"NZ":                         47,
   654  		"PE":                         48,
   655  		"PH":                         49,
   656  		"PK":                         50,
   657  		"PL":                         51,
   658  		"PT":                         52,
   659  		"RO":                         53,
   660  		"RS":                         54,
   661  		"RU":                         55,
   662  		"SA":                         56,
   663  		"SE":                         57,
   664  		"SG":                         58,
   665  		"SI":                         59,
   666  		"SK":                         60,
   667  		"TH":                         61,
   668  		"TR":                         62,
   669  		"TW":                         63,
   670  		"UA":                         64,
   671  		"US":                         65,
   672  		"VE":                         66,
   673  		"VN":                         67,
   674  		"ZA":                         68,
   675  	}
   676  )
   677  
   678  func (x Model_HolidayRegion) Enum() *Model_HolidayRegion {
   679  	p := new(Model_HolidayRegion)
   680  	*p = x
   681  	return p
   682  }
   683  
   684  func (x Model_HolidayRegion) String() string {
   685  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   686  }
   687  
   688  func (Model_HolidayRegion) Descriptor() protoreflect.EnumDescriptor {
   689  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[5].Descriptor()
   690  }
   691  
   692  func (Model_HolidayRegion) Type() protoreflect.EnumType {
   693  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[5]
   694  }
   695  
   696  func (x Model_HolidayRegion) Number() protoreflect.EnumNumber {
   697  	return protoreflect.EnumNumber(x)
   698  }
   699  
   700  // Deprecated: Use Model_HolidayRegion.Descriptor instead.
   701  func (Model_HolidayRegion) EnumDescriptor() ([]byte, []int) {
   702  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 5}
   703  }
   704  
   705  // Indicates the learning rate optimization strategy to use.
   706  type Model_LearnRateStrategy int32
   707  
   708  const (
   709  	Model_LEARN_RATE_STRATEGY_UNSPECIFIED Model_LearnRateStrategy = 0
   710  	// Use line search to determine learning rate.
   711  	Model_LINE_SEARCH Model_LearnRateStrategy = 1
   712  	// Use a constant learning rate.
   713  	Model_CONSTANT Model_LearnRateStrategy = 2
   714  )
   715  
   716  // Enum value maps for Model_LearnRateStrategy.
   717  var (
   718  	Model_LearnRateStrategy_name = map[int32]string{
   719  		0: "LEARN_RATE_STRATEGY_UNSPECIFIED",
   720  		1: "LINE_SEARCH",
   721  		2: "CONSTANT",
   722  	}
   723  	Model_LearnRateStrategy_value = map[string]int32{
   724  		"LEARN_RATE_STRATEGY_UNSPECIFIED": 0,
   725  		"LINE_SEARCH":                     1,
   726  		"CONSTANT":                        2,
   727  	}
   728  )
   729  
   730  func (x Model_LearnRateStrategy) Enum() *Model_LearnRateStrategy {
   731  	p := new(Model_LearnRateStrategy)
   732  	*p = x
   733  	return p
   734  }
   735  
   736  func (x Model_LearnRateStrategy) String() string {
   737  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   738  }
   739  
   740  func (Model_LearnRateStrategy) Descriptor() protoreflect.EnumDescriptor {
   741  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[6].Descriptor()
   742  }
   743  
   744  func (Model_LearnRateStrategy) Type() protoreflect.EnumType {
   745  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[6]
   746  }
   747  
   748  func (x Model_LearnRateStrategy) Number() protoreflect.EnumNumber {
   749  	return protoreflect.EnumNumber(x)
   750  }
   751  
   752  // Deprecated: Use Model_LearnRateStrategy.Descriptor instead.
   753  func (Model_LearnRateStrategy) EnumDescriptor() ([]byte, []int) {
   754  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 6}
   755  }
   756  
   757  // Indicates the optimization strategy used for training.
   758  type Model_OptimizationStrategy int32
   759  
   760  const (
   761  	Model_OPTIMIZATION_STRATEGY_UNSPECIFIED Model_OptimizationStrategy = 0
   762  	// Uses an iterative batch gradient descent algorithm.
   763  	Model_BATCH_GRADIENT_DESCENT Model_OptimizationStrategy = 1
   764  	// Uses a normal equation to solve linear regression problem.
   765  	Model_NORMAL_EQUATION Model_OptimizationStrategy = 2
   766  )
   767  
   768  // Enum value maps for Model_OptimizationStrategy.
   769  var (
   770  	Model_OptimizationStrategy_name = map[int32]string{
   771  		0: "OPTIMIZATION_STRATEGY_UNSPECIFIED",
   772  		1: "BATCH_GRADIENT_DESCENT",
   773  		2: "NORMAL_EQUATION",
   774  	}
   775  	Model_OptimizationStrategy_value = map[string]int32{
   776  		"OPTIMIZATION_STRATEGY_UNSPECIFIED": 0,
   777  		"BATCH_GRADIENT_DESCENT":            1,
   778  		"NORMAL_EQUATION":                   2,
   779  	}
   780  )
   781  
   782  func (x Model_OptimizationStrategy) Enum() *Model_OptimizationStrategy {
   783  	p := new(Model_OptimizationStrategy)
   784  	*p = x
   785  	return p
   786  }
   787  
   788  func (x Model_OptimizationStrategy) String() string {
   789  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   790  }
   791  
   792  func (Model_OptimizationStrategy) Descriptor() protoreflect.EnumDescriptor {
   793  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[7].Descriptor()
   794  }
   795  
   796  func (Model_OptimizationStrategy) Type() protoreflect.EnumType {
   797  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[7]
   798  }
   799  
   800  func (x Model_OptimizationStrategy) Number() protoreflect.EnumNumber {
   801  	return protoreflect.EnumNumber(x)
   802  }
   803  
   804  // Deprecated: Use Model_OptimizationStrategy.Descriptor instead.
   805  func (Model_OptimizationStrategy) EnumDescriptor() ([]byte, []int) {
   806  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 7}
   807  }
   808  
   809  // Indicates the training algorithm to use for matrix factorization models.
   810  type Model_FeedbackType int32
   811  
   812  const (
   813  	Model_FEEDBACK_TYPE_UNSPECIFIED Model_FeedbackType = 0
   814  	// Use weighted-als for implicit feedback problems.
   815  	Model_IMPLICIT Model_FeedbackType = 1
   816  	// Use nonweighted-als for explicit feedback problems.
   817  	Model_EXPLICIT Model_FeedbackType = 2
   818  )
   819  
   820  // Enum value maps for Model_FeedbackType.
   821  var (
   822  	Model_FeedbackType_name = map[int32]string{
   823  		0: "FEEDBACK_TYPE_UNSPECIFIED",
   824  		1: "IMPLICIT",
   825  		2: "EXPLICIT",
   826  	}
   827  	Model_FeedbackType_value = map[string]int32{
   828  		"FEEDBACK_TYPE_UNSPECIFIED": 0,
   829  		"IMPLICIT":                  1,
   830  		"EXPLICIT":                  2,
   831  	}
   832  )
   833  
   834  func (x Model_FeedbackType) Enum() *Model_FeedbackType {
   835  	p := new(Model_FeedbackType)
   836  	*p = x
   837  	return p
   838  }
   839  
   840  func (x Model_FeedbackType) String() string {
   841  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   842  }
   843  
   844  func (Model_FeedbackType) Descriptor() protoreflect.EnumDescriptor {
   845  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[8].Descriptor()
   846  }
   847  
   848  func (Model_FeedbackType) Type() protoreflect.EnumType {
   849  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[8]
   850  }
   851  
   852  func (x Model_FeedbackType) Number() protoreflect.EnumNumber {
   853  	return protoreflect.EnumNumber(x)
   854  }
   855  
   856  // Deprecated: Use Model_FeedbackType.Descriptor instead.
   857  func (Model_FeedbackType) EnumDescriptor() ([]byte, []int) {
   858  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 8}
   859  }
   860  
   861  type Model_SeasonalPeriod_SeasonalPeriodType int32
   862  
   863  const (
   864  	Model_SeasonalPeriod_SEASONAL_PERIOD_TYPE_UNSPECIFIED Model_SeasonalPeriod_SeasonalPeriodType = 0
   865  	// No seasonality
   866  	Model_SeasonalPeriod_NO_SEASONALITY Model_SeasonalPeriod_SeasonalPeriodType = 1
   867  	// Daily period, 24 hours.
   868  	Model_SeasonalPeriod_DAILY Model_SeasonalPeriod_SeasonalPeriodType = 2
   869  	// Weekly period, 7 days.
   870  	Model_SeasonalPeriod_WEEKLY Model_SeasonalPeriod_SeasonalPeriodType = 3
   871  	// Monthly period, 30 days or irregular.
   872  	Model_SeasonalPeriod_MONTHLY Model_SeasonalPeriod_SeasonalPeriodType = 4
   873  	// Quarterly period, 90 days or irregular.
   874  	Model_SeasonalPeriod_QUARTERLY Model_SeasonalPeriod_SeasonalPeriodType = 5
   875  	// Yearly period, 365 days or irregular.
   876  	Model_SeasonalPeriod_YEARLY Model_SeasonalPeriod_SeasonalPeriodType = 6
   877  )
   878  
   879  // Enum value maps for Model_SeasonalPeriod_SeasonalPeriodType.
   880  var (
   881  	Model_SeasonalPeriod_SeasonalPeriodType_name = map[int32]string{
   882  		0: "SEASONAL_PERIOD_TYPE_UNSPECIFIED",
   883  		1: "NO_SEASONALITY",
   884  		2: "DAILY",
   885  		3: "WEEKLY",
   886  		4: "MONTHLY",
   887  		5: "QUARTERLY",
   888  		6: "YEARLY",
   889  	}
   890  	Model_SeasonalPeriod_SeasonalPeriodType_value = map[string]int32{
   891  		"SEASONAL_PERIOD_TYPE_UNSPECIFIED": 0,
   892  		"NO_SEASONALITY":                   1,
   893  		"DAILY":                            2,
   894  		"WEEKLY":                           3,
   895  		"MONTHLY":                          4,
   896  		"QUARTERLY":                        5,
   897  		"YEARLY":                           6,
   898  	}
   899  )
   900  
   901  func (x Model_SeasonalPeriod_SeasonalPeriodType) Enum() *Model_SeasonalPeriod_SeasonalPeriodType {
   902  	p := new(Model_SeasonalPeriod_SeasonalPeriodType)
   903  	*p = x
   904  	return p
   905  }
   906  
   907  func (x Model_SeasonalPeriod_SeasonalPeriodType) String() string {
   908  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   909  }
   910  
   911  func (Model_SeasonalPeriod_SeasonalPeriodType) Descriptor() protoreflect.EnumDescriptor {
   912  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[9].Descriptor()
   913  }
   914  
   915  func (Model_SeasonalPeriod_SeasonalPeriodType) Type() protoreflect.EnumType {
   916  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[9]
   917  }
   918  
   919  func (x Model_SeasonalPeriod_SeasonalPeriodType) Number() protoreflect.EnumNumber {
   920  	return protoreflect.EnumNumber(x)
   921  }
   922  
   923  // Deprecated: Use Model_SeasonalPeriod_SeasonalPeriodType.Descriptor instead.
   924  func (Model_SeasonalPeriod_SeasonalPeriodType) EnumDescriptor() ([]byte, []int) {
   925  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 0, 0}
   926  }
   927  
   928  // Indicates the method used to initialize the centroids for KMeans
   929  // clustering algorithm.
   930  type Model_KmeansEnums_KmeansInitializationMethod int32
   931  
   932  const (
   933  	// Unspecified initialization method.
   934  	Model_KmeansEnums_KMEANS_INITIALIZATION_METHOD_UNSPECIFIED Model_KmeansEnums_KmeansInitializationMethod = 0
   935  	// Initializes the centroids randomly.
   936  	Model_KmeansEnums_RANDOM Model_KmeansEnums_KmeansInitializationMethod = 1
   937  	// Initializes the centroids using data specified in
   938  	// kmeans_initialization_column.
   939  	Model_KmeansEnums_CUSTOM Model_KmeansEnums_KmeansInitializationMethod = 2
   940  	// Initializes with kmeans++.
   941  	Model_KmeansEnums_KMEANS_PLUS_PLUS Model_KmeansEnums_KmeansInitializationMethod = 3
   942  )
   943  
   944  // Enum value maps for Model_KmeansEnums_KmeansInitializationMethod.
   945  var (
   946  	Model_KmeansEnums_KmeansInitializationMethod_name = map[int32]string{
   947  		0: "KMEANS_INITIALIZATION_METHOD_UNSPECIFIED",
   948  		1: "RANDOM",
   949  		2: "CUSTOM",
   950  		3: "KMEANS_PLUS_PLUS",
   951  	}
   952  	Model_KmeansEnums_KmeansInitializationMethod_value = map[string]int32{
   953  		"KMEANS_INITIALIZATION_METHOD_UNSPECIFIED": 0,
   954  		"RANDOM":           1,
   955  		"CUSTOM":           2,
   956  		"KMEANS_PLUS_PLUS": 3,
   957  	}
   958  )
   959  
   960  func (x Model_KmeansEnums_KmeansInitializationMethod) Enum() *Model_KmeansEnums_KmeansInitializationMethod {
   961  	p := new(Model_KmeansEnums_KmeansInitializationMethod)
   962  	*p = x
   963  	return p
   964  }
   965  
   966  func (x Model_KmeansEnums_KmeansInitializationMethod) String() string {
   967  	return protoimpl.X.EnumStringOf(x.Descriptor(), protoreflect.EnumNumber(x))
   968  }
   969  
   970  func (Model_KmeansEnums_KmeansInitializationMethod) Descriptor() protoreflect.EnumDescriptor {
   971  	return file_google_cloud_bigquery_v2_model_proto_enumTypes[10].Descriptor()
   972  }
   973  
   974  func (Model_KmeansEnums_KmeansInitializationMethod) Type() protoreflect.EnumType {
   975  	return &file_google_cloud_bigquery_v2_model_proto_enumTypes[10]
   976  }
   977  
   978  func (x Model_KmeansEnums_KmeansInitializationMethod) Number() protoreflect.EnumNumber {
   979  	return protoreflect.EnumNumber(x)
   980  }
   981  
   982  // Deprecated: Use Model_KmeansEnums_KmeansInitializationMethod.Descriptor instead.
   983  func (Model_KmeansEnums_KmeansInitializationMethod) EnumDescriptor() ([]byte, []int) {
   984  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 1, 0}
   985  }
   986  
   987  type Model struct {
   988  	state         protoimpl.MessageState
   989  	sizeCache     protoimpl.SizeCache
   990  	unknownFields protoimpl.UnknownFields
   991  
   992  	// Output only. A hash of this resource.
   993  	Etag string `protobuf:"bytes,1,opt,name=etag,proto3" json:"etag,omitempty"`
   994  	// Required. Unique identifier for this model.
   995  	ModelReference *ModelReference `protobuf:"bytes,2,opt,name=model_reference,json=modelReference,proto3" json:"model_reference,omitempty"`
   996  	// Output only. The time when this model was created, in millisecs since the epoch.
   997  	CreationTime int64 `protobuf:"varint,5,opt,name=creation_time,json=creationTime,proto3" json:"creation_time,omitempty"`
   998  	// Output only. The time when this model was last modified, in millisecs since the epoch.
   999  	LastModifiedTime int64 `protobuf:"varint,6,opt,name=last_modified_time,json=lastModifiedTime,proto3" json:"last_modified_time,omitempty"`
  1000  	// Optional. A user-friendly description of this model.
  1001  	Description string `protobuf:"bytes,12,opt,name=description,proto3" json:"description,omitempty"`
  1002  	// Optional. A descriptive name for this model.
  1003  	FriendlyName string `protobuf:"bytes,14,opt,name=friendly_name,json=friendlyName,proto3" json:"friendly_name,omitempty"`
  1004  	// The labels associated with this model. You can use these to organize
  1005  	// and group your models. Label keys and values can be no longer
  1006  	// than 63 characters, can only contain lowercase letters, numeric
  1007  	// characters, underscores and dashes. International characters are allowed.
  1008  	// Label values are optional. Label keys must start with a letter and each
  1009  	// label in the list must have a different key.
  1010  	Labels map[string]string `protobuf:"bytes,15,rep,name=labels,proto3" json:"labels,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"bytes,2,opt,name=value,proto3"`
  1011  	// Optional. The time when this model expires, in milliseconds since the epoch.
  1012  	// If not present, the model will persist indefinitely. Expired models
  1013  	// will be deleted and their storage reclaimed.  The defaultTableExpirationMs
  1014  	// property of the encapsulating dataset can be used to set a default
  1015  	// expirationTime on newly created models.
  1016  	ExpirationTime int64 `protobuf:"varint,16,opt,name=expiration_time,json=expirationTime,proto3" json:"expiration_time,omitempty"`
  1017  	// Output only. The geographic location where the model resides. This value
  1018  	// is inherited from the dataset.
  1019  	Location string `protobuf:"bytes,13,opt,name=location,proto3" json:"location,omitempty"`
  1020  	// Custom encryption configuration (e.g., Cloud KMS keys). This shows the
  1021  	// encryption configuration of the model data while stored in BigQuery
  1022  	// storage. This field can be used with PatchModel to update encryption key
  1023  	// for an already encrypted model.
  1024  	EncryptionConfiguration *EncryptionConfiguration `protobuf:"bytes,17,opt,name=encryption_configuration,json=encryptionConfiguration,proto3" json:"encryption_configuration,omitempty"`
  1025  	// Output only. Type of the model resource.
  1026  	ModelType Model_ModelType `protobuf:"varint,7,opt,name=model_type,json=modelType,proto3,enum=google.cloud.bigquery.v2.Model_ModelType" json:"model_type,omitempty"`
  1027  	// Output only. Information for all training runs in increasing order of start_time.
  1028  	TrainingRuns []*Model_TrainingRun `protobuf:"bytes,9,rep,name=training_runs,json=trainingRuns,proto3" json:"training_runs,omitempty"`
  1029  	// Output only. Input feature columns that were used to train this model.
  1030  	FeatureColumns []*StandardSqlField `protobuf:"bytes,10,rep,name=feature_columns,json=featureColumns,proto3" json:"feature_columns,omitempty"`
  1031  	// Output only. Label columns that were used to train this model.
  1032  	// The output of the model will have a "predicted_" prefix to these columns.
  1033  	LabelColumns []*StandardSqlField `protobuf:"bytes,11,rep,name=label_columns,json=labelColumns,proto3" json:"label_columns,omitempty"`
  1034  	// The best trial_id across all training runs.
  1035  	//
  1036  	// Deprecated: Do not use.
  1037  	BestTrialId int64 `protobuf:"varint,19,opt,name=best_trial_id,json=bestTrialId,proto3" json:"best_trial_id,omitempty"`
  1038  }
  1039  
  1040  func (x *Model) Reset() {
  1041  	*x = Model{}
  1042  	if protoimpl.UnsafeEnabled {
  1043  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[0]
  1044  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1045  		ms.StoreMessageInfo(mi)
  1046  	}
  1047  }
  1048  
  1049  func (x *Model) String() string {
  1050  	return protoimpl.X.MessageStringOf(x)
  1051  }
  1052  
  1053  func (*Model) ProtoMessage() {}
  1054  
  1055  func (x *Model) ProtoReflect() protoreflect.Message {
  1056  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[0]
  1057  	if protoimpl.UnsafeEnabled && x != nil {
  1058  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1059  		if ms.LoadMessageInfo() == nil {
  1060  			ms.StoreMessageInfo(mi)
  1061  		}
  1062  		return ms
  1063  	}
  1064  	return mi.MessageOf(x)
  1065  }
  1066  
  1067  // Deprecated: Use Model.ProtoReflect.Descriptor instead.
  1068  func (*Model) Descriptor() ([]byte, []int) {
  1069  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0}
  1070  }
  1071  
  1072  func (x *Model) GetEtag() string {
  1073  	if x != nil {
  1074  		return x.Etag
  1075  	}
  1076  	return ""
  1077  }
  1078  
  1079  func (x *Model) GetModelReference() *ModelReference {
  1080  	if x != nil {
  1081  		return x.ModelReference
  1082  	}
  1083  	return nil
  1084  }
  1085  
  1086  func (x *Model) GetCreationTime() int64 {
  1087  	if x != nil {
  1088  		return x.CreationTime
  1089  	}
  1090  	return 0
  1091  }
  1092  
  1093  func (x *Model) GetLastModifiedTime() int64 {
  1094  	if x != nil {
  1095  		return x.LastModifiedTime
  1096  	}
  1097  	return 0
  1098  }
  1099  
  1100  func (x *Model) GetDescription() string {
  1101  	if x != nil {
  1102  		return x.Description
  1103  	}
  1104  	return ""
  1105  }
  1106  
  1107  func (x *Model) GetFriendlyName() string {
  1108  	if x != nil {
  1109  		return x.FriendlyName
  1110  	}
  1111  	return ""
  1112  }
  1113  
  1114  func (x *Model) GetLabels() map[string]string {
  1115  	if x != nil {
  1116  		return x.Labels
  1117  	}
  1118  	return nil
  1119  }
  1120  
  1121  func (x *Model) GetExpirationTime() int64 {
  1122  	if x != nil {
  1123  		return x.ExpirationTime
  1124  	}
  1125  	return 0
  1126  }
  1127  
  1128  func (x *Model) GetLocation() string {
  1129  	if x != nil {
  1130  		return x.Location
  1131  	}
  1132  	return ""
  1133  }
  1134  
  1135  func (x *Model) GetEncryptionConfiguration() *EncryptionConfiguration {
  1136  	if x != nil {
  1137  		return x.EncryptionConfiguration
  1138  	}
  1139  	return nil
  1140  }
  1141  
  1142  func (x *Model) GetModelType() Model_ModelType {
  1143  	if x != nil {
  1144  		return x.ModelType
  1145  	}
  1146  	return Model_MODEL_TYPE_UNSPECIFIED
  1147  }
  1148  
  1149  func (x *Model) GetTrainingRuns() []*Model_TrainingRun {
  1150  	if x != nil {
  1151  		return x.TrainingRuns
  1152  	}
  1153  	return nil
  1154  }
  1155  
  1156  func (x *Model) GetFeatureColumns() []*StandardSqlField {
  1157  	if x != nil {
  1158  		return x.FeatureColumns
  1159  	}
  1160  	return nil
  1161  }
  1162  
  1163  func (x *Model) GetLabelColumns() []*StandardSqlField {
  1164  	if x != nil {
  1165  		return x.LabelColumns
  1166  	}
  1167  	return nil
  1168  }
  1169  
  1170  // Deprecated: Do not use.
  1171  func (x *Model) GetBestTrialId() int64 {
  1172  	if x != nil {
  1173  		return x.BestTrialId
  1174  	}
  1175  	return 0
  1176  }
  1177  
  1178  type GetModelRequest struct {
  1179  	state         protoimpl.MessageState
  1180  	sizeCache     protoimpl.SizeCache
  1181  	unknownFields protoimpl.UnknownFields
  1182  
  1183  	// Required. Project ID of the requested model.
  1184  	ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
  1185  	// Required. Dataset ID of the requested model.
  1186  	DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
  1187  	// Required. Model ID of the requested model.
  1188  	ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"`
  1189  }
  1190  
  1191  func (x *GetModelRequest) Reset() {
  1192  	*x = GetModelRequest{}
  1193  	if protoimpl.UnsafeEnabled {
  1194  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[1]
  1195  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1196  		ms.StoreMessageInfo(mi)
  1197  	}
  1198  }
  1199  
  1200  func (x *GetModelRequest) String() string {
  1201  	return protoimpl.X.MessageStringOf(x)
  1202  }
  1203  
  1204  func (*GetModelRequest) ProtoMessage() {}
  1205  
  1206  func (x *GetModelRequest) ProtoReflect() protoreflect.Message {
  1207  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[1]
  1208  	if protoimpl.UnsafeEnabled && x != nil {
  1209  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1210  		if ms.LoadMessageInfo() == nil {
  1211  			ms.StoreMessageInfo(mi)
  1212  		}
  1213  		return ms
  1214  	}
  1215  	return mi.MessageOf(x)
  1216  }
  1217  
  1218  // Deprecated: Use GetModelRequest.ProtoReflect.Descriptor instead.
  1219  func (*GetModelRequest) Descriptor() ([]byte, []int) {
  1220  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{1}
  1221  }
  1222  
  1223  func (x *GetModelRequest) GetProjectId() string {
  1224  	if x != nil {
  1225  		return x.ProjectId
  1226  	}
  1227  	return ""
  1228  }
  1229  
  1230  func (x *GetModelRequest) GetDatasetId() string {
  1231  	if x != nil {
  1232  		return x.DatasetId
  1233  	}
  1234  	return ""
  1235  }
  1236  
  1237  func (x *GetModelRequest) GetModelId() string {
  1238  	if x != nil {
  1239  		return x.ModelId
  1240  	}
  1241  	return ""
  1242  }
  1243  
  1244  type PatchModelRequest struct {
  1245  	state         protoimpl.MessageState
  1246  	sizeCache     protoimpl.SizeCache
  1247  	unknownFields protoimpl.UnknownFields
  1248  
  1249  	// Required. Project ID of the model to patch.
  1250  	ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
  1251  	// Required. Dataset ID of the model to patch.
  1252  	DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
  1253  	// Required. Model ID of the model to patch.
  1254  	ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"`
  1255  	// Required. Patched model.
  1256  	// Follows RFC5789 patch semantics. Missing fields are not updated.
  1257  	// To clear a field, explicitly set to default value.
  1258  	Model *Model `protobuf:"bytes,4,opt,name=model,proto3" json:"model,omitempty"`
  1259  }
  1260  
  1261  func (x *PatchModelRequest) Reset() {
  1262  	*x = PatchModelRequest{}
  1263  	if protoimpl.UnsafeEnabled {
  1264  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[2]
  1265  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1266  		ms.StoreMessageInfo(mi)
  1267  	}
  1268  }
  1269  
  1270  func (x *PatchModelRequest) String() string {
  1271  	return protoimpl.X.MessageStringOf(x)
  1272  }
  1273  
  1274  func (*PatchModelRequest) ProtoMessage() {}
  1275  
  1276  func (x *PatchModelRequest) ProtoReflect() protoreflect.Message {
  1277  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[2]
  1278  	if protoimpl.UnsafeEnabled && x != nil {
  1279  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1280  		if ms.LoadMessageInfo() == nil {
  1281  			ms.StoreMessageInfo(mi)
  1282  		}
  1283  		return ms
  1284  	}
  1285  	return mi.MessageOf(x)
  1286  }
  1287  
  1288  // Deprecated: Use PatchModelRequest.ProtoReflect.Descriptor instead.
  1289  func (*PatchModelRequest) Descriptor() ([]byte, []int) {
  1290  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{2}
  1291  }
  1292  
  1293  func (x *PatchModelRequest) GetProjectId() string {
  1294  	if x != nil {
  1295  		return x.ProjectId
  1296  	}
  1297  	return ""
  1298  }
  1299  
  1300  func (x *PatchModelRequest) GetDatasetId() string {
  1301  	if x != nil {
  1302  		return x.DatasetId
  1303  	}
  1304  	return ""
  1305  }
  1306  
  1307  func (x *PatchModelRequest) GetModelId() string {
  1308  	if x != nil {
  1309  		return x.ModelId
  1310  	}
  1311  	return ""
  1312  }
  1313  
  1314  func (x *PatchModelRequest) GetModel() *Model {
  1315  	if x != nil {
  1316  		return x.Model
  1317  	}
  1318  	return nil
  1319  }
  1320  
  1321  type DeleteModelRequest struct {
  1322  	state         protoimpl.MessageState
  1323  	sizeCache     protoimpl.SizeCache
  1324  	unknownFields protoimpl.UnknownFields
  1325  
  1326  	// Required. Project ID of the model to delete.
  1327  	ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
  1328  	// Required. Dataset ID of the model to delete.
  1329  	DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
  1330  	// Required. Model ID of the model to delete.
  1331  	ModelId string `protobuf:"bytes,3,opt,name=model_id,json=modelId,proto3" json:"model_id,omitempty"`
  1332  }
  1333  
  1334  func (x *DeleteModelRequest) Reset() {
  1335  	*x = DeleteModelRequest{}
  1336  	if protoimpl.UnsafeEnabled {
  1337  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[3]
  1338  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1339  		ms.StoreMessageInfo(mi)
  1340  	}
  1341  }
  1342  
  1343  func (x *DeleteModelRequest) String() string {
  1344  	return protoimpl.X.MessageStringOf(x)
  1345  }
  1346  
  1347  func (*DeleteModelRequest) ProtoMessage() {}
  1348  
  1349  func (x *DeleteModelRequest) ProtoReflect() protoreflect.Message {
  1350  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[3]
  1351  	if protoimpl.UnsafeEnabled && x != nil {
  1352  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1353  		if ms.LoadMessageInfo() == nil {
  1354  			ms.StoreMessageInfo(mi)
  1355  		}
  1356  		return ms
  1357  	}
  1358  	return mi.MessageOf(x)
  1359  }
  1360  
  1361  // Deprecated: Use DeleteModelRequest.ProtoReflect.Descriptor instead.
  1362  func (*DeleteModelRequest) Descriptor() ([]byte, []int) {
  1363  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{3}
  1364  }
  1365  
  1366  func (x *DeleteModelRequest) GetProjectId() string {
  1367  	if x != nil {
  1368  		return x.ProjectId
  1369  	}
  1370  	return ""
  1371  }
  1372  
  1373  func (x *DeleteModelRequest) GetDatasetId() string {
  1374  	if x != nil {
  1375  		return x.DatasetId
  1376  	}
  1377  	return ""
  1378  }
  1379  
  1380  func (x *DeleteModelRequest) GetModelId() string {
  1381  	if x != nil {
  1382  		return x.ModelId
  1383  	}
  1384  	return ""
  1385  }
  1386  
  1387  type ListModelsRequest struct {
  1388  	state         protoimpl.MessageState
  1389  	sizeCache     protoimpl.SizeCache
  1390  	unknownFields protoimpl.UnknownFields
  1391  
  1392  	// Required. Project ID of the models to list.
  1393  	ProjectId string `protobuf:"bytes,1,opt,name=project_id,json=projectId,proto3" json:"project_id,omitempty"`
  1394  	// Required. Dataset ID of the models to list.
  1395  	DatasetId string `protobuf:"bytes,2,opt,name=dataset_id,json=datasetId,proto3" json:"dataset_id,omitempty"`
  1396  	// The maximum number of results to return in a single response page.
  1397  	// Leverage the page tokens to iterate through the entire collection.
  1398  	MaxResults *wrapperspb.UInt32Value `protobuf:"bytes,3,opt,name=max_results,json=maxResults,proto3" json:"max_results,omitempty"`
  1399  	// Page token, returned by a previous call to request the next page of
  1400  	// results
  1401  	PageToken string `protobuf:"bytes,4,opt,name=page_token,json=pageToken,proto3" json:"page_token,omitempty"`
  1402  }
  1403  
  1404  func (x *ListModelsRequest) Reset() {
  1405  	*x = ListModelsRequest{}
  1406  	if protoimpl.UnsafeEnabled {
  1407  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[4]
  1408  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1409  		ms.StoreMessageInfo(mi)
  1410  	}
  1411  }
  1412  
  1413  func (x *ListModelsRequest) String() string {
  1414  	return protoimpl.X.MessageStringOf(x)
  1415  }
  1416  
  1417  func (*ListModelsRequest) ProtoMessage() {}
  1418  
  1419  func (x *ListModelsRequest) ProtoReflect() protoreflect.Message {
  1420  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[4]
  1421  	if protoimpl.UnsafeEnabled && x != nil {
  1422  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1423  		if ms.LoadMessageInfo() == nil {
  1424  			ms.StoreMessageInfo(mi)
  1425  		}
  1426  		return ms
  1427  	}
  1428  	return mi.MessageOf(x)
  1429  }
  1430  
  1431  // Deprecated: Use ListModelsRequest.ProtoReflect.Descriptor instead.
  1432  func (*ListModelsRequest) Descriptor() ([]byte, []int) {
  1433  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{4}
  1434  }
  1435  
  1436  func (x *ListModelsRequest) GetProjectId() string {
  1437  	if x != nil {
  1438  		return x.ProjectId
  1439  	}
  1440  	return ""
  1441  }
  1442  
  1443  func (x *ListModelsRequest) GetDatasetId() string {
  1444  	if x != nil {
  1445  		return x.DatasetId
  1446  	}
  1447  	return ""
  1448  }
  1449  
  1450  func (x *ListModelsRequest) GetMaxResults() *wrapperspb.UInt32Value {
  1451  	if x != nil {
  1452  		return x.MaxResults
  1453  	}
  1454  	return nil
  1455  }
  1456  
  1457  func (x *ListModelsRequest) GetPageToken() string {
  1458  	if x != nil {
  1459  		return x.PageToken
  1460  	}
  1461  	return ""
  1462  }
  1463  
  1464  type ListModelsResponse struct {
  1465  	state         protoimpl.MessageState
  1466  	sizeCache     protoimpl.SizeCache
  1467  	unknownFields protoimpl.UnknownFields
  1468  
  1469  	// Models in the requested dataset. Only the following fields are populated:
  1470  	// model_reference, model_type, creation_time, last_modified_time and
  1471  	// labels.
  1472  	Models []*Model `protobuf:"bytes,1,rep,name=models,proto3" json:"models,omitempty"`
  1473  	// A token to request the next page of results.
  1474  	NextPageToken string `protobuf:"bytes,2,opt,name=next_page_token,json=nextPageToken,proto3" json:"next_page_token,omitempty"`
  1475  }
  1476  
  1477  func (x *ListModelsResponse) Reset() {
  1478  	*x = ListModelsResponse{}
  1479  	if protoimpl.UnsafeEnabled {
  1480  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[5]
  1481  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1482  		ms.StoreMessageInfo(mi)
  1483  	}
  1484  }
  1485  
  1486  func (x *ListModelsResponse) String() string {
  1487  	return protoimpl.X.MessageStringOf(x)
  1488  }
  1489  
  1490  func (*ListModelsResponse) ProtoMessage() {}
  1491  
  1492  func (x *ListModelsResponse) ProtoReflect() protoreflect.Message {
  1493  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[5]
  1494  	if protoimpl.UnsafeEnabled && x != nil {
  1495  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1496  		if ms.LoadMessageInfo() == nil {
  1497  			ms.StoreMessageInfo(mi)
  1498  		}
  1499  		return ms
  1500  	}
  1501  	return mi.MessageOf(x)
  1502  }
  1503  
  1504  // Deprecated: Use ListModelsResponse.ProtoReflect.Descriptor instead.
  1505  func (*ListModelsResponse) Descriptor() ([]byte, []int) {
  1506  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{5}
  1507  }
  1508  
  1509  func (x *ListModelsResponse) GetModels() []*Model {
  1510  	if x != nil {
  1511  		return x.Models
  1512  	}
  1513  	return nil
  1514  }
  1515  
  1516  func (x *ListModelsResponse) GetNextPageToken() string {
  1517  	if x != nil {
  1518  		return x.NextPageToken
  1519  	}
  1520  	return ""
  1521  }
  1522  
  1523  type Model_SeasonalPeriod struct {
  1524  	state         protoimpl.MessageState
  1525  	sizeCache     protoimpl.SizeCache
  1526  	unknownFields protoimpl.UnknownFields
  1527  }
  1528  
  1529  func (x *Model_SeasonalPeriod) Reset() {
  1530  	*x = Model_SeasonalPeriod{}
  1531  	if protoimpl.UnsafeEnabled {
  1532  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[6]
  1533  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1534  		ms.StoreMessageInfo(mi)
  1535  	}
  1536  }
  1537  
  1538  func (x *Model_SeasonalPeriod) String() string {
  1539  	return protoimpl.X.MessageStringOf(x)
  1540  }
  1541  
  1542  func (*Model_SeasonalPeriod) ProtoMessage() {}
  1543  
  1544  func (x *Model_SeasonalPeriod) ProtoReflect() protoreflect.Message {
  1545  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[6]
  1546  	if protoimpl.UnsafeEnabled && x != nil {
  1547  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1548  		if ms.LoadMessageInfo() == nil {
  1549  			ms.StoreMessageInfo(mi)
  1550  		}
  1551  		return ms
  1552  	}
  1553  	return mi.MessageOf(x)
  1554  }
  1555  
  1556  // Deprecated: Use Model_SeasonalPeriod.ProtoReflect.Descriptor instead.
  1557  func (*Model_SeasonalPeriod) Descriptor() ([]byte, []int) {
  1558  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 0}
  1559  }
  1560  
  1561  type Model_KmeansEnums struct {
  1562  	state         protoimpl.MessageState
  1563  	sizeCache     protoimpl.SizeCache
  1564  	unknownFields protoimpl.UnknownFields
  1565  }
  1566  
  1567  func (x *Model_KmeansEnums) Reset() {
  1568  	*x = Model_KmeansEnums{}
  1569  	if protoimpl.UnsafeEnabled {
  1570  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[7]
  1571  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1572  		ms.StoreMessageInfo(mi)
  1573  	}
  1574  }
  1575  
  1576  func (x *Model_KmeansEnums) String() string {
  1577  	return protoimpl.X.MessageStringOf(x)
  1578  }
  1579  
  1580  func (*Model_KmeansEnums) ProtoMessage() {}
  1581  
  1582  func (x *Model_KmeansEnums) ProtoReflect() protoreflect.Message {
  1583  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[7]
  1584  	if protoimpl.UnsafeEnabled && x != nil {
  1585  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1586  		if ms.LoadMessageInfo() == nil {
  1587  			ms.StoreMessageInfo(mi)
  1588  		}
  1589  		return ms
  1590  	}
  1591  	return mi.MessageOf(x)
  1592  }
  1593  
  1594  // Deprecated: Use Model_KmeansEnums.ProtoReflect.Descriptor instead.
  1595  func (*Model_KmeansEnums) Descriptor() ([]byte, []int) {
  1596  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 1}
  1597  }
  1598  
  1599  // Evaluation metrics for regression and explicit feedback type matrix
  1600  // factorization models.
  1601  type Model_RegressionMetrics struct {
  1602  	state         protoimpl.MessageState
  1603  	sizeCache     protoimpl.SizeCache
  1604  	unknownFields protoimpl.UnknownFields
  1605  
  1606  	// Mean absolute error.
  1607  	MeanAbsoluteError *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=mean_absolute_error,json=meanAbsoluteError,proto3" json:"mean_absolute_error,omitempty"`
  1608  	// Mean squared error.
  1609  	MeanSquaredError *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_error,json=meanSquaredError,proto3" json:"mean_squared_error,omitempty"`
  1610  	// Mean squared log error.
  1611  	MeanSquaredLogError *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=mean_squared_log_error,json=meanSquaredLogError,proto3" json:"mean_squared_log_error,omitempty"`
  1612  	// Median absolute error.
  1613  	MedianAbsoluteError *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=median_absolute_error,json=medianAbsoluteError,proto3" json:"median_absolute_error,omitempty"`
  1614  	// R^2 score. This corresponds to r2_score in ML.EVALUATE.
  1615  	RSquared *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=r_squared,json=rSquared,proto3" json:"r_squared,omitempty"`
  1616  }
  1617  
  1618  func (x *Model_RegressionMetrics) Reset() {
  1619  	*x = Model_RegressionMetrics{}
  1620  	if protoimpl.UnsafeEnabled {
  1621  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[8]
  1622  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1623  		ms.StoreMessageInfo(mi)
  1624  	}
  1625  }
  1626  
  1627  func (x *Model_RegressionMetrics) String() string {
  1628  	return protoimpl.X.MessageStringOf(x)
  1629  }
  1630  
  1631  func (*Model_RegressionMetrics) ProtoMessage() {}
  1632  
  1633  func (x *Model_RegressionMetrics) ProtoReflect() protoreflect.Message {
  1634  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[8]
  1635  	if protoimpl.UnsafeEnabled && x != nil {
  1636  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1637  		if ms.LoadMessageInfo() == nil {
  1638  			ms.StoreMessageInfo(mi)
  1639  		}
  1640  		return ms
  1641  	}
  1642  	return mi.MessageOf(x)
  1643  }
  1644  
  1645  // Deprecated: Use Model_RegressionMetrics.ProtoReflect.Descriptor instead.
  1646  func (*Model_RegressionMetrics) Descriptor() ([]byte, []int) {
  1647  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 2}
  1648  }
  1649  
  1650  func (x *Model_RegressionMetrics) GetMeanAbsoluteError() *wrapperspb.DoubleValue {
  1651  	if x != nil {
  1652  		return x.MeanAbsoluteError
  1653  	}
  1654  	return nil
  1655  }
  1656  
  1657  func (x *Model_RegressionMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue {
  1658  	if x != nil {
  1659  		return x.MeanSquaredError
  1660  	}
  1661  	return nil
  1662  }
  1663  
  1664  func (x *Model_RegressionMetrics) GetMeanSquaredLogError() *wrapperspb.DoubleValue {
  1665  	if x != nil {
  1666  		return x.MeanSquaredLogError
  1667  	}
  1668  	return nil
  1669  }
  1670  
  1671  func (x *Model_RegressionMetrics) GetMedianAbsoluteError() *wrapperspb.DoubleValue {
  1672  	if x != nil {
  1673  		return x.MedianAbsoluteError
  1674  	}
  1675  	return nil
  1676  }
  1677  
  1678  func (x *Model_RegressionMetrics) GetRSquared() *wrapperspb.DoubleValue {
  1679  	if x != nil {
  1680  		return x.RSquared
  1681  	}
  1682  	return nil
  1683  }
  1684  
  1685  // Aggregate metrics for classification/classifier models. For multi-class
  1686  // models, the metrics are either macro-averaged or micro-averaged. When
  1687  // macro-averaged, the metrics are calculated for each label and then an
  1688  // unweighted average is taken of those values. When micro-averaged, the
  1689  // metric is calculated globally by counting the total number of correctly
  1690  // predicted rows.
  1691  type Model_AggregateClassificationMetrics struct {
  1692  	state         protoimpl.MessageState
  1693  	sizeCache     protoimpl.SizeCache
  1694  	unknownFields protoimpl.UnknownFields
  1695  
  1696  	// Precision is the fraction of actual positive predictions that had
  1697  	// positive actual labels. For multiclass this is a macro-averaged
  1698  	// metric treating each class as a binary classifier.
  1699  	Precision *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=precision,proto3" json:"precision,omitempty"`
  1700  	// Recall is the fraction of actual positive labels that were given a
  1701  	// positive prediction. For multiclass this is a macro-averaged metric.
  1702  	Recall *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=recall,proto3" json:"recall,omitempty"`
  1703  	// Accuracy is the fraction of predictions given the correct label. For
  1704  	// multiclass this is a micro-averaged metric.
  1705  	Accuracy *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=accuracy,proto3" json:"accuracy,omitempty"`
  1706  	// Threshold at which the metrics are computed. For binary
  1707  	// classification models this is the positive class threshold.
  1708  	// For multi-class classfication models this is the confidence
  1709  	// threshold.
  1710  	Threshold *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=threshold,proto3" json:"threshold,omitempty"`
  1711  	// The F1 score is an average of recall and precision. For multiclass
  1712  	// this is a macro-averaged metric.
  1713  	F1Score *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=f1_score,json=f1Score,proto3" json:"f1_score,omitempty"`
  1714  	// Logarithmic Loss. For multiclass this is a macro-averaged metric.
  1715  	LogLoss *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=log_loss,json=logLoss,proto3" json:"log_loss,omitempty"`
  1716  	// Area Under a ROC Curve. For multiclass this is a macro-averaged
  1717  	// metric.
  1718  	RocAuc *wrapperspb.DoubleValue `protobuf:"bytes,7,opt,name=roc_auc,json=rocAuc,proto3" json:"roc_auc,omitempty"`
  1719  }
  1720  
  1721  func (x *Model_AggregateClassificationMetrics) Reset() {
  1722  	*x = Model_AggregateClassificationMetrics{}
  1723  	if protoimpl.UnsafeEnabled {
  1724  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[9]
  1725  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1726  		ms.StoreMessageInfo(mi)
  1727  	}
  1728  }
  1729  
  1730  func (x *Model_AggregateClassificationMetrics) String() string {
  1731  	return protoimpl.X.MessageStringOf(x)
  1732  }
  1733  
  1734  func (*Model_AggregateClassificationMetrics) ProtoMessage() {}
  1735  
  1736  func (x *Model_AggregateClassificationMetrics) ProtoReflect() protoreflect.Message {
  1737  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[9]
  1738  	if protoimpl.UnsafeEnabled && x != nil {
  1739  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1740  		if ms.LoadMessageInfo() == nil {
  1741  			ms.StoreMessageInfo(mi)
  1742  		}
  1743  		return ms
  1744  	}
  1745  	return mi.MessageOf(x)
  1746  }
  1747  
  1748  // Deprecated: Use Model_AggregateClassificationMetrics.ProtoReflect.Descriptor instead.
  1749  func (*Model_AggregateClassificationMetrics) Descriptor() ([]byte, []int) {
  1750  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 3}
  1751  }
  1752  
  1753  func (x *Model_AggregateClassificationMetrics) GetPrecision() *wrapperspb.DoubleValue {
  1754  	if x != nil {
  1755  		return x.Precision
  1756  	}
  1757  	return nil
  1758  }
  1759  
  1760  func (x *Model_AggregateClassificationMetrics) GetRecall() *wrapperspb.DoubleValue {
  1761  	if x != nil {
  1762  		return x.Recall
  1763  	}
  1764  	return nil
  1765  }
  1766  
  1767  func (x *Model_AggregateClassificationMetrics) GetAccuracy() *wrapperspb.DoubleValue {
  1768  	if x != nil {
  1769  		return x.Accuracy
  1770  	}
  1771  	return nil
  1772  }
  1773  
  1774  func (x *Model_AggregateClassificationMetrics) GetThreshold() *wrapperspb.DoubleValue {
  1775  	if x != nil {
  1776  		return x.Threshold
  1777  	}
  1778  	return nil
  1779  }
  1780  
  1781  func (x *Model_AggregateClassificationMetrics) GetF1Score() *wrapperspb.DoubleValue {
  1782  	if x != nil {
  1783  		return x.F1Score
  1784  	}
  1785  	return nil
  1786  }
  1787  
  1788  func (x *Model_AggregateClassificationMetrics) GetLogLoss() *wrapperspb.DoubleValue {
  1789  	if x != nil {
  1790  		return x.LogLoss
  1791  	}
  1792  	return nil
  1793  }
  1794  
  1795  func (x *Model_AggregateClassificationMetrics) GetRocAuc() *wrapperspb.DoubleValue {
  1796  	if x != nil {
  1797  		return x.RocAuc
  1798  	}
  1799  	return nil
  1800  }
  1801  
  1802  // Evaluation metrics for binary classification/classifier models.
  1803  type Model_BinaryClassificationMetrics struct {
  1804  	state         protoimpl.MessageState
  1805  	sizeCache     protoimpl.SizeCache
  1806  	unknownFields protoimpl.UnknownFields
  1807  
  1808  	// Aggregate classification metrics.
  1809  	AggregateClassificationMetrics *Model_AggregateClassificationMetrics `protobuf:"bytes,1,opt,name=aggregate_classification_metrics,json=aggregateClassificationMetrics,proto3" json:"aggregate_classification_metrics,omitempty"`
  1810  	// Binary confusion matrix at multiple thresholds.
  1811  	BinaryConfusionMatrixList []*Model_BinaryClassificationMetrics_BinaryConfusionMatrix `protobuf:"bytes,2,rep,name=binary_confusion_matrix_list,json=binaryConfusionMatrixList,proto3" json:"binary_confusion_matrix_list,omitempty"`
  1812  	// Label representing the positive class.
  1813  	PositiveLabel string `protobuf:"bytes,3,opt,name=positive_label,json=positiveLabel,proto3" json:"positive_label,omitempty"`
  1814  	// Label representing the negative class.
  1815  	NegativeLabel string `protobuf:"bytes,4,opt,name=negative_label,json=negativeLabel,proto3" json:"negative_label,omitempty"`
  1816  }
  1817  
  1818  func (x *Model_BinaryClassificationMetrics) Reset() {
  1819  	*x = Model_BinaryClassificationMetrics{}
  1820  	if protoimpl.UnsafeEnabled {
  1821  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[10]
  1822  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1823  		ms.StoreMessageInfo(mi)
  1824  	}
  1825  }
  1826  
  1827  func (x *Model_BinaryClassificationMetrics) String() string {
  1828  	return protoimpl.X.MessageStringOf(x)
  1829  }
  1830  
  1831  func (*Model_BinaryClassificationMetrics) ProtoMessage() {}
  1832  
  1833  func (x *Model_BinaryClassificationMetrics) ProtoReflect() protoreflect.Message {
  1834  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[10]
  1835  	if protoimpl.UnsafeEnabled && x != nil {
  1836  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1837  		if ms.LoadMessageInfo() == nil {
  1838  			ms.StoreMessageInfo(mi)
  1839  		}
  1840  		return ms
  1841  	}
  1842  	return mi.MessageOf(x)
  1843  }
  1844  
  1845  // Deprecated: Use Model_BinaryClassificationMetrics.ProtoReflect.Descriptor instead.
  1846  func (*Model_BinaryClassificationMetrics) Descriptor() ([]byte, []int) {
  1847  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 4}
  1848  }
  1849  
  1850  func (x *Model_BinaryClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics {
  1851  	if x != nil {
  1852  		return x.AggregateClassificationMetrics
  1853  	}
  1854  	return nil
  1855  }
  1856  
  1857  func (x *Model_BinaryClassificationMetrics) GetBinaryConfusionMatrixList() []*Model_BinaryClassificationMetrics_BinaryConfusionMatrix {
  1858  	if x != nil {
  1859  		return x.BinaryConfusionMatrixList
  1860  	}
  1861  	return nil
  1862  }
  1863  
  1864  func (x *Model_BinaryClassificationMetrics) GetPositiveLabel() string {
  1865  	if x != nil {
  1866  		return x.PositiveLabel
  1867  	}
  1868  	return ""
  1869  }
  1870  
  1871  func (x *Model_BinaryClassificationMetrics) GetNegativeLabel() string {
  1872  	if x != nil {
  1873  		return x.NegativeLabel
  1874  	}
  1875  	return ""
  1876  }
  1877  
  1878  // Evaluation metrics for multi-class classification/classifier models.
  1879  type Model_MultiClassClassificationMetrics struct {
  1880  	state         protoimpl.MessageState
  1881  	sizeCache     protoimpl.SizeCache
  1882  	unknownFields protoimpl.UnknownFields
  1883  
  1884  	// Aggregate classification metrics.
  1885  	AggregateClassificationMetrics *Model_AggregateClassificationMetrics `protobuf:"bytes,1,opt,name=aggregate_classification_metrics,json=aggregateClassificationMetrics,proto3" json:"aggregate_classification_metrics,omitempty"`
  1886  	// Confusion matrix at different thresholds.
  1887  	ConfusionMatrixList []*Model_MultiClassClassificationMetrics_ConfusionMatrix `protobuf:"bytes,2,rep,name=confusion_matrix_list,json=confusionMatrixList,proto3" json:"confusion_matrix_list,omitempty"`
  1888  }
  1889  
  1890  func (x *Model_MultiClassClassificationMetrics) Reset() {
  1891  	*x = Model_MultiClassClassificationMetrics{}
  1892  	if protoimpl.UnsafeEnabled {
  1893  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[11]
  1894  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1895  		ms.StoreMessageInfo(mi)
  1896  	}
  1897  }
  1898  
  1899  func (x *Model_MultiClassClassificationMetrics) String() string {
  1900  	return protoimpl.X.MessageStringOf(x)
  1901  }
  1902  
  1903  func (*Model_MultiClassClassificationMetrics) ProtoMessage() {}
  1904  
  1905  func (x *Model_MultiClassClassificationMetrics) ProtoReflect() protoreflect.Message {
  1906  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[11]
  1907  	if protoimpl.UnsafeEnabled && x != nil {
  1908  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1909  		if ms.LoadMessageInfo() == nil {
  1910  			ms.StoreMessageInfo(mi)
  1911  		}
  1912  		return ms
  1913  	}
  1914  	return mi.MessageOf(x)
  1915  }
  1916  
  1917  // Deprecated: Use Model_MultiClassClassificationMetrics.ProtoReflect.Descriptor instead.
  1918  func (*Model_MultiClassClassificationMetrics) Descriptor() ([]byte, []int) {
  1919  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 5}
  1920  }
  1921  
  1922  func (x *Model_MultiClassClassificationMetrics) GetAggregateClassificationMetrics() *Model_AggregateClassificationMetrics {
  1923  	if x != nil {
  1924  		return x.AggregateClassificationMetrics
  1925  	}
  1926  	return nil
  1927  }
  1928  
  1929  func (x *Model_MultiClassClassificationMetrics) GetConfusionMatrixList() []*Model_MultiClassClassificationMetrics_ConfusionMatrix {
  1930  	if x != nil {
  1931  		return x.ConfusionMatrixList
  1932  	}
  1933  	return nil
  1934  }
  1935  
  1936  // Evaluation metrics for clustering models.
  1937  type Model_ClusteringMetrics struct {
  1938  	state         protoimpl.MessageState
  1939  	sizeCache     protoimpl.SizeCache
  1940  	unknownFields protoimpl.UnknownFields
  1941  
  1942  	// Davies-Bouldin index.
  1943  	DaviesBouldinIndex *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=davies_bouldin_index,json=daviesBouldinIndex,proto3" json:"davies_bouldin_index,omitempty"`
  1944  	// Mean of squared distances between each sample to its cluster centroid.
  1945  	MeanSquaredDistance *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_distance,json=meanSquaredDistance,proto3" json:"mean_squared_distance,omitempty"`
  1946  	// Information for all clusters.
  1947  	Clusters []*Model_ClusteringMetrics_Cluster `protobuf:"bytes,3,rep,name=clusters,proto3" json:"clusters,omitempty"`
  1948  }
  1949  
  1950  func (x *Model_ClusteringMetrics) Reset() {
  1951  	*x = Model_ClusteringMetrics{}
  1952  	if protoimpl.UnsafeEnabled {
  1953  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[12]
  1954  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1955  		ms.StoreMessageInfo(mi)
  1956  	}
  1957  }
  1958  
  1959  func (x *Model_ClusteringMetrics) String() string {
  1960  	return protoimpl.X.MessageStringOf(x)
  1961  }
  1962  
  1963  func (*Model_ClusteringMetrics) ProtoMessage() {}
  1964  
  1965  func (x *Model_ClusteringMetrics) ProtoReflect() protoreflect.Message {
  1966  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[12]
  1967  	if protoimpl.UnsafeEnabled && x != nil {
  1968  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  1969  		if ms.LoadMessageInfo() == nil {
  1970  			ms.StoreMessageInfo(mi)
  1971  		}
  1972  		return ms
  1973  	}
  1974  	return mi.MessageOf(x)
  1975  }
  1976  
  1977  // Deprecated: Use Model_ClusteringMetrics.ProtoReflect.Descriptor instead.
  1978  func (*Model_ClusteringMetrics) Descriptor() ([]byte, []int) {
  1979  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 6}
  1980  }
  1981  
  1982  func (x *Model_ClusteringMetrics) GetDaviesBouldinIndex() *wrapperspb.DoubleValue {
  1983  	if x != nil {
  1984  		return x.DaviesBouldinIndex
  1985  	}
  1986  	return nil
  1987  }
  1988  
  1989  func (x *Model_ClusteringMetrics) GetMeanSquaredDistance() *wrapperspb.DoubleValue {
  1990  	if x != nil {
  1991  		return x.MeanSquaredDistance
  1992  	}
  1993  	return nil
  1994  }
  1995  
  1996  func (x *Model_ClusteringMetrics) GetClusters() []*Model_ClusteringMetrics_Cluster {
  1997  	if x != nil {
  1998  		return x.Clusters
  1999  	}
  2000  	return nil
  2001  }
  2002  
  2003  // Evaluation metrics used by weighted-ALS models specified by
  2004  // feedback_type=implicit.
  2005  type Model_RankingMetrics struct {
  2006  	state         protoimpl.MessageState
  2007  	sizeCache     protoimpl.SizeCache
  2008  	unknownFields protoimpl.UnknownFields
  2009  
  2010  	// Calculates a precision per user for all the items by ranking them and
  2011  	// then averages all the precisions across all the users.
  2012  	MeanAveragePrecision *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=mean_average_precision,json=meanAveragePrecision,proto3" json:"mean_average_precision,omitempty"`
  2013  	// Similar to the mean squared error computed in regression and explicit
  2014  	// recommendation models except instead of computing the rating directly,
  2015  	// the output from evaluate is computed against a preference which is 1 or 0
  2016  	// depending on if the rating exists or not.
  2017  	MeanSquaredError *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=mean_squared_error,json=meanSquaredError,proto3" json:"mean_squared_error,omitempty"`
  2018  	// A metric to determine the goodness of a ranking calculated from the
  2019  	// predicted confidence by comparing it to an ideal rank measured by the
  2020  	// original ratings.
  2021  	NormalizedDiscountedCumulativeGain *wrapperspb.DoubleValue `protobuf:"bytes,3,opt,name=normalized_discounted_cumulative_gain,json=normalizedDiscountedCumulativeGain,proto3" json:"normalized_discounted_cumulative_gain,omitempty"`
  2022  	// Determines the goodness of a ranking by computing the percentile rank
  2023  	// from the predicted confidence and dividing it by the original rank.
  2024  	AverageRank *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=average_rank,json=averageRank,proto3" json:"average_rank,omitempty"`
  2025  }
  2026  
  2027  func (x *Model_RankingMetrics) Reset() {
  2028  	*x = Model_RankingMetrics{}
  2029  	if protoimpl.UnsafeEnabled {
  2030  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[13]
  2031  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2032  		ms.StoreMessageInfo(mi)
  2033  	}
  2034  }
  2035  
  2036  func (x *Model_RankingMetrics) String() string {
  2037  	return protoimpl.X.MessageStringOf(x)
  2038  }
  2039  
  2040  func (*Model_RankingMetrics) ProtoMessage() {}
  2041  
  2042  func (x *Model_RankingMetrics) ProtoReflect() protoreflect.Message {
  2043  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[13]
  2044  	if protoimpl.UnsafeEnabled && x != nil {
  2045  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2046  		if ms.LoadMessageInfo() == nil {
  2047  			ms.StoreMessageInfo(mi)
  2048  		}
  2049  		return ms
  2050  	}
  2051  	return mi.MessageOf(x)
  2052  }
  2053  
  2054  // Deprecated: Use Model_RankingMetrics.ProtoReflect.Descriptor instead.
  2055  func (*Model_RankingMetrics) Descriptor() ([]byte, []int) {
  2056  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 7}
  2057  }
  2058  
  2059  func (x *Model_RankingMetrics) GetMeanAveragePrecision() *wrapperspb.DoubleValue {
  2060  	if x != nil {
  2061  		return x.MeanAveragePrecision
  2062  	}
  2063  	return nil
  2064  }
  2065  
  2066  func (x *Model_RankingMetrics) GetMeanSquaredError() *wrapperspb.DoubleValue {
  2067  	if x != nil {
  2068  		return x.MeanSquaredError
  2069  	}
  2070  	return nil
  2071  }
  2072  
  2073  func (x *Model_RankingMetrics) GetNormalizedDiscountedCumulativeGain() *wrapperspb.DoubleValue {
  2074  	if x != nil {
  2075  		return x.NormalizedDiscountedCumulativeGain
  2076  	}
  2077  	return nil
  2078  }
  2079  
  2080  func (x *Model_RankingMetrics) GetAverageRank() *wrapperspb.DoubleValue {
  2081  	if x != nil {
  2082  		return x.AverageRank
  2083  	}
  2084  	return nil
  2085  }
  2086  
  2087  // Model evaluation metrics for ARIMA forecasting models.
  2088  type Model_ArimaForecastingMetrics struct {
  2089  	state         protoimpl.MessageState
  2090  	sizeCache     protoimpl.SizeCache
  2091  	unknownFields protoimpl.UnknownFields
  2092  
  2093  	// Non-seasonal order.
  2094  	//
  2095  	// Deprecated: Do not use.
  2096  	NonSeasonalOrder []*Model_ArimaOrder `protobuf:"bytes,1,rep,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
  2097  	// Arima model fitting metrics.
  2098  	//
  2099  	// Deprecated: Do not use.
  2100  	ArimaFittingMetrics []*Model_ArimaFittingMetrics `protobuf:"bytes,2,rep,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"`
  2101  	// Seasonal periods. Repeated because multiple periods are supported for one
  2102  	// time series.
  2103  	//
  2104  	// Deprecated: Do not use.
  2105  	SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,3,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
  2106  	// Whether Arima model fitted with drift or not. It is always false when d
  2107  	// is not 1.
  2108  	//
  2109  	// Deprecated: Do not use.
  2110  	HasDrift []bool `protobuf:"varint,4,rep,packed,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"`
  2111  	// Id to differentiate different time series for the large-scale case.
  2112  	//
  2113  	// Deprecated: Do not use.
  2114  	TimeSeriesId []string `protobuf:"bytes,5,rep,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"`
  2115  	// Repeated as there can be many metric sets (one for each model) in
  2116  	// auto-arima and the large-scale case.
  2117  	ArimaSingleModelForecastingMetrics []*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics `protobuf:"bytes,6,rep,name=arima_single_model_forecasting_metrics,json=arimaSingleModelForecastingMetrics,proto3" json:"arima_single_model_forecasting_metrics,omitempty"`
  2118  }
  2119  
  2120  func (x *Model_ArimaForecastingMetrics) Reset() {
  2121  	*x = Model_ArimaForecastingMetrics{}
  2122  	if protoimpl.UnsafeEnabled {
  2123  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[14]
  2124  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2125  		ms.StoreMessageInfo(mi)
  2126  	}
  2127  }
  2128  
  2129  func (x *Model_ArimaForecastingMetrics) String() string {
  2130  	return protoimpl.X.MessageStringOf(x)
  2131  }
  2132  
  2133  func (*Model_ArimaForecastingMetrics) ProtoMessage() {}
  2134  
  2135  func (x *Model_ArimaForecastingMetrics) ProtoReflect() protoreflect.Message {
  2136  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[14]
  2137  	if protoimpl.UnsafeEnabled && x != nil {
  2138  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2139  		if ms.LoadMessageInfo() == nil {
  2140  			ms.StoreMessageInfo(mi)
  2141  		}
  2142  		return ms
  2143  	}
  2144  	return mi.MessageOf(x)
  2145  }
  2146  
  2147  // Deprecated: Use Model_ArimaForecastingMetrics.ProtoReflect.Descriptor instead.
  2148  func (*Model_ArimaForecastingMetrics) Descriptor() ([]byte, []int) {
  2149  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 8}
  2150  }
  2151  
  2152  // Deprecated: Do not use.
  2153  func (x *Model_ArimaForecastingMetrics) GetNonSeasonalOrder() []*Model_ArimaOrder {
  2154  	if x != nil {
  2155  		return x.NonSeasonalOrder
  2156  	}
  2157  	return nil
  2158  }
  2159  
  2160  // Deprecated: Do not use.
  2161  func (x *Model_ArimaForecastingMetrics) GetArimaFittingMetrics() []*Model_ArimaFittingMetrics {
  2162  	if x != nil {
  2163  		return x.ArimaFittingMetrics
  2164  	}
  2165  	return nil
  2166  }
  2167  
  2168  // Deprecated: Do not use.
  2169  func (x *Model_ArimaForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType {
  2170  	if x != nil {
  2171  		return x.SeasonalPeriods
  2172  	}
  2173  	return nil
  2174  }
  2175  
  2176  // Deprecated: Do not use.
  2177  func (x *Model_ArimaForecastingMetrics) GetHasDrift() []bool {
  2178  	if x != nil {
  2179  		return x.HasDrift
  2180  	}
  2181  	return nil
  2182  }
  2183  
  2184  // Deprecated: Do not use.
  2185  func (x *Model_ArimaForecastingMetrics) GetTimeSeriesId() []string {
  2186  	if x != nil {
  2187  		return x.TimeSeriesId
  2188  	}
  2189  	return nil
  2190  }
  2191  
  2192  func (x *Model_ArimaForecastingMetrics) GetArimaSingleModelForecastingMetrics() []*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics {
  2193  	if x != nil {
  2194  		return x.ArimaSingleModelForecastingMetrics
  2195  	}
  2196  	return nil
  2197  }
  2198  
  2199  // Evaluation metrics of a model. These are either computed on all training
  2200  // data or just the eval data based on whether eval data was used during
  2201  // training. These are not present for imported models.
  2202  type Model_EvaluationMetrics struct {
  2203  	state         protoimpl.MessageState
  2204  	sizeCache     protoimpl.SizeCache
  2205  	unknownFields protoimpl.UnknownFields
  2206  
  2207  	// Types that are assignable to Metrics:
  2208  	//	*Model_EvaluationMetrics_RegressionMetrics
  2209  	//	*Model_EvaluationMetrics_BinaryClassificationMetrics
  2210  	//	*Model_EvaluationMetrics_MultiClassClassificationMetrics
  2211  	//	*Model_EvaluationMetrics_ClusteringMetrics
  2212  	//	*Model_EvaluationMetrics_RankingMetrics
  2213  	//	*Model_EvaluationMetrics_ArimaForecastingMetrics
  2214  	Metrics isModel_EvaluationMetrics_Metrics `protobuf_oneof:"metrics"`
  2215  }
  2216  
  2217  func (x *Model_EvaluationMetrics) Reset() {
  2218  	*x = Model_EvaluationMetrics{}
  2219  	if protoimpl.UnsafeEnabled {
  2220  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[15]
  2221  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2222  		ms.StoreMessageInfo(mi)
  2223  	}
  2224  }
  2225  
  2226  func (x *Model_EvaluationMetrics) String() string {
  2227  	return protoimpl.X.MessageStringOf(x)
  2228  }
  2229  
  2230  func (*Model_EvaluationMetrics) ProtoMessage() {}
  2231  
  2232  func (x *Model_EvaluationMetrics) ProtoReflect() protoreflect.Message {
  2233  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[15]
  2234  	if protoimpl.UnsafeEnabled && x != nil {
  2235  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2236  		if ms.LoadMessageInfo() == nil {
  2237  			ms.StoreMessageInfo(mi)
  2238  		}
  2239  		return ms
  2240  	}
  2241  	return mi.MessageOf(x)
  2242  }
  2243  
  2244  // Deprecated: Use Model_EvaluationMetrics.ProtoReflect.Descriptor instead.
  2245  func (*Model_EvaluationMetrics) Descriptor() ([]byte, []int) {
  2246  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 9}
  2247  }
  2248  
  2249  func (m *Model_EvaluationMetrics) GetMetrics() isModel_EvaluationMetrics_Metrics {
  2250  	if m != nil {
  2251  		return m.Metrics
  2252  	}
  2253  	return nil
  2254  }
  2255  
  2256  func (x *Model_EvaluationMetrics) GetRegressionMetrics() *Model_RegressionMetrics {
  2257  	if x, ok := x.GetMetrics().(*Model_EvaluationMetrics_RegressionMetrics); ok {
  2258  		return x.RegressionMetrics
  2259  	}
  2260  	return nil
  2261  }
  2262  
  2263  func (x *Model_EvaluationMetrics) GetBinaryClassificationMetrics() *Model_BinaryClassificationMetrics {
  2264  	if x, ok := x.GetMetrics().(*Model_EvaluationMetrics_BinaryClassificationMetrics); ok {
  2265  		return x.BinaryClassificationMetrics
  2266  	}
  2267  	return nil
  2268  }
  2269  
  2270  func (x *Model_EvaluationMetrics) GetMultiClassClassificationMetrics() *Model_MultiClassClassificationMetrics {
  2271  	if x, ok := x.GetMetrics().(*Model_EvaluationMetrics_MultiClassClassificationMetrics); ok {
  2272  		return x.MultiClassClassificationMetrics
  2273  	}
  2274  	return nil
  2275  }
  2276  
  2277  func (x *Model_EvaluationMetrics) GetClusteringMetrics() *Model_ClusteringMetrics {
  2278  	if x, ok := x.GetMetrics().(*Model_EvaluationMetrics_ClusteringMetrics); ok {
  2279  		return x.ClusteringMetrics
  2280  	}
  2281  	return nil
  2282  }
  2283  
  2284  func (x *Model_EvaluationMetrics) GetRankingMetrics() *Model_RankingMetrics {
  2285  	if x, ok := x.GetMetrics().(*Model_EvaluationMetrics_RankingMetrics); ok {
  2286  		return x.RankingMetrics
  2287  	}
  2288  	return nil
  2289  }
  2290  
  2291  func (x *Model_EvaluationMetrics) GetArimaForecastingMetrics() *Model_ArimaForecastingMetrics {
  2292  	if x, ok := x.GetMetrics().(*Model_EvaluationMetrics_ArimaForecastingMetrics); ok {
  2293  		return x.ArimaForecastingMetrics
  2294  	}
  2295  	return nil
  2296  }
  2297  
  2298  type isModel_EvaluationMetrics_Metrics interface {
  2299  	isModel_EvaluationMetrics_Metrics()
  2300  }
  2301  
  2302  type Model_EvaluationMetrics_RegressionMetrics struct {
  2303  	// Populated for regression models and explicit feedback type matrix
  2304  	// factorization models.
  2305  	RegressionMetrics *Model_RegressionMetrics `protobuf:"bytes,1,opt,name=regression_metrics,json=regressionMetrics,proto3,oneof"`
  2306  }
  2307  
  2308  type Model_EvaluationMetrics_BinaryClassificationMetrics struct {
  2309  	// Populated for binary classification/classifier models.
  2310  	BinaryClassificationMetrics *Model_BinaryClassificationMetrics `protobuf:"bytes,2,opt,name=binary_classification_metrics,json=binaryClassificationMetrics,proto3,oneof"`
  2311  }
  2312  
  2313  type Model_EvaluationMetrics_MultiClassClassificationMetrics struct {
  2314  	// Populated for multi-class classification/classifier models.
  2315  	MultiClassClassificationMetrics *Model_MultiClassClassificationMetrics `protobuf:"bytes,3,opt,name=multi_class_classification_metrics,json=multiClassClassificationMetrics,proto3,oneof"`
  2316  }
  2317  
  2318  type Model_EvaluationMetrics_ClusteringMetrics struct {
  2319  	// Populated for clustering models.
  2320  	ClusteringMetrics *Model_ClusteringMetrics `protobuf:"bytes,4,opt,name=clustering_metrics,json=clusteringMetrics,proto3,oneof"`
  2321  }
  2322  
  2323  type Model_EvaluationMetrics_RankingMetrics struct {
  2324  	// Populated for implicit feedback type matrix factorization models.
  2325  	RankingMetrics *Model_RankingMetrics `protobuf:"bytes,5,opt,name=ranking_metrics,json=rankingMetrics,proto3,oneof"`
  2326  }
  2327  
  2328  type Model_EvaluationMetrics_ArimaForecastingMetrics struct {
  2329  	// Populated for ARIMA models.
  2330  	ArimaForecastingMetrics *Model_ArimaForecastingMetrics `protobuf:"bytes,6,opt,name=arima_forecasting_metrics,json=arimaForecastingMetrics,proto3,oneof"`
  2331  }
  2332  
  2333  func (*Model_EvaluationMetrics_RegressionMetrics) isModel_EvaluationMetrics_Metrics() {}
  2334  
  2335  func (*Model_EvaluationMetrics_BinaryClassificationMetrics) isModel_EvaluationMetrics_Metrics() {}
  2336  
  2337  func (*Model_EvaluationMetrics_MultiClassClassificationMetrics) isModel_EvaluationMetrics_Metrics() {}
  2338  
  2339  func (*Model_EvaluationMetrics_ClusteringMetrics) isModel_EvaluationMetrics_Metrics() {}
  2340  
  2341  func (*Model_EvaluationMetrics_RankingMetrics) isModel_EvaluationMetrics_Metrics() {}
  2342  
  2343  func (*Model_EvaluationMetrics_ArimaForecastingMetrics) isModel_EvaluationMetrics_Metrics() {}
  2344  
  2345  // Data split result. This contains references to the training and evaluation
  2346  // data tables that were used to train the model.
  2347  type Model_DataSplitResult struct {
  2348  	state         protoimpl.MessageState
  2349  	sizeCache     protoimpl.SizeCache
  2350  	unknownFields protoimpl.UnknownFields
  2351  
  2352  	// Table reference of the training data after split.
  2353  	TrainingTable *TableReference `protobuf:"bytes,1,opt,name=training_table,json=trainingTable,proto3" json:"training_table,omitempty"`
  2354  	// Table reference of the evaluation data after split.
  2355  	EvaluationTable *TableReference `protobuf:"bytes,2,opt,name=evaluation_table,json=evaluationTable,proto3" json:"evaluation_table,omitempty"`
  2356  }
  2357  
  2358  func (x *Model_DataSplitResult) Reset() {
  2359  	*x = Model_DataSplitResult{}
  2360  	if protoimpl.UnsafeEnabled {
  2361  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[16]
  2362  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2363  		ms.StoreMessageInfo(mi)
  2364  	}
  2365  }
  2366  
  2367  func (x *Model_DataSplitResult) String() string {
  2368  	return protoimpl.X.MessageStringOf(x)
  2369  }
  2370  
  2371  func (*Model_DataSplitResult) ProtoMessage() {}
  2372  
  2373  func (x *Model_DataSplitResult) ProtoReflect() protoreflect.Message {
  2374  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[16]
  2375  	if protoimpl.UnsafeEnabled && x != nil {
  2376  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2377  		if ms.LoadMessageInfo() == nil {
  2378  			ms.StoreMessageInfo(mi)
  2379  		}
  2380  		return ms
  2381  	}
  2382  	return mi.MessageOf(x)
  2383  }
  2384  
  2385  // Deprecated: Use Model_DataSplitResult.ProtoReflect.Descriptor instead.
  2386  func (*Model_DataSplitResult) Descriptor() ([]byte, []int) {
  2387  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 10}
  2388  }
  2389  
  2390  func (x *Model_DataSplitResult) GetTrainingTable() *TableReference {
  2391  	if x != nil {
  2392  		return x.TrainingTable
  2393  	}
  2394  	return nil
  2395  }
  2396  
  2397  func (x *Model_DataSplitResult) GetEvaluationTable() *TableReference {
  2398  	if x != nil {
  2399  		return x.EvaluationTable
  2400  	}
  2401  	return nil
  2402  }
  2403  
  2404  // Arima order, can be used for both non-seasonal and seasonal parts.
  2405  type Model_ArimaOrder struct {
  2406  	state         protoimpl.MessageState
  2407  	sizeCache     protoimpl.SizeCache
  2408  	unknownFields protoimpl.UnknownFields
  2409  
  2410  	// Order of the autoregressive part.
  2411  	P int64 `protobuf:"varint,1,opt,name=p,proto3" json:"p,omitempty"`
  2412  	// Order of the differencing part.
  2413  	D int64 `protobuf:"varint,2,opt,name=d,proto3" json:"d,omitempty"`
  2414  	// Order of the moving-average part.
  2415  	Q int64 `protobuf:"varint,3,opt,name=q,proto3" json:"q,omitempty"`
  2416  }
  2417  
  2418  func (x *Model_ArimaOrder) Reset() {
  2419  	*x = Model_ArimaOrder{}
  2420  	if protoimpl.UnsafeEnabled {
  2421  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[17]
  2422  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2423  		ms.StoreMessageInfo(mi)
  2424  	}
  2425  }
  2426  
  2427  func (x *Model_ArimaOrder) String() string {
  2428  	return protoimpl.X.MessageStringOf(x)
  2429  }
  2430  
  2431  func (*Model_ArimaOrder) ProtoMessage() {}
  2432  
  2433  func (x *Model_ArimaOrder) ProtoReflect() protoreflect.Message {
  2434  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[17]
  2435  	if protoimpl.UnsafeEnabled && x != nil {
  2436  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2437  		if ms.LoadMessageInfo() == nil {
  2438  			ms.StoreMessageInfo(mi)
  2439  		}
  2440  		return ms
  2441  	}
  2442  	return mi.MessageOf(x)
  2443  }
  2444  
  2445  // Deprecated: Use Model_ArimaOrder.ProtoReflect.Descriptor instead.
  2446  func (*Model_ArimaOrder) Descriptor() ([]byte, []int) {
  2447  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 11}
  2448  }
  2449  
  2450  func (x *Model_ArimaOrder) GetP() int64 {
  2451  	if x != nil {
  2452  		return x.P
  2453  	}
  2454  	return 0
  2455  }
  2456  
  2457  func (x *Model_ArimaOrder) GetD() int64 {
  2458  	if x != nil {
  2459  		return x.D
  2460  	}
  2461  	return 0
  2462  }
  2463  
  2464  func (x *Model_ArimaOrder) GetQ() int64 {
  2465  	if x != nil {
  2466  		return x.Q
  2467  	}
  2468  	return 0
  2469  }
  2470  
  2471  // ARIMA model fitting metrics.
  2472  type Model_ArimaFittingMetrics struct {
  2473  	state         protoimpl.MessageState
  2474  	sizeCache     protoimpl.SizeCache
  2475  	unknownFields protoimpl.UnknownFields
  2476  
  2477  	// Log-likelihood.
  2478  	LogLikelihood float64 `protobuf:"fixed64,1,opt,name=log_likelihood,json=logLikelihood,proto3" json:"log_likelihood,omitempty"`
  2479  	// AIC.
  2480  	Aic float64 `protobuf:"fixed64,2,opt,name=aic,proto3" json:"aic,omitempty"`
  2481  	// Variance.
  2482  	Variance float64 `protobuf:"fixed64,3,opt,name=variance,proto3" json:"variance,omitempty"`
  2483  }
  2484  
  2485  func (x *Model_ArimaFittingMetrics) Reset() {
  2486  	*x = Model_ArimaFittingMetrics{}
  2487  	if protoimpl.UnsafeEnabled {
  2488  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[18]
  2489  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2490  		ms.StoreMessageInfo(mi)
  2491  	}
  2492  }
  2493  
  2494  func (x *Model_ArimaFittingMetrics) String() string {
  2495  	return protoimpl.X.MessageStringOf(x)
  2496  }
  2497  
  2498  func (*Model_ArimaFittingMetrics) ProtoMessage() {}
  2499  
  2500  func (x *Model_ArimaFittingMetrics) ProtoReflect() protoreflect.Message {
  2501  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[18]
  2502  	if protoimpl.UnsafeEnabled && x != nil {
  2503  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2504  		if ms.LoadMessageInfo() == nil {
  2505  			ms.StoreMessageInfo(mi)
  2506  		}
  2507  		return ms
  2508  	}
  2509  	return mi.MessageOf(x)
  2510  }
  2511  
  2512  // Deprecated: Use Model_ArimaFittingMetrics.ProtoReflect.Descriptor instead.
  2513  func (*Model_ArimaFittingMetrics) Descriptor() ([]byte, []int) {
  2514  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 12}
  2515  }
  2516  
  2517  func (x *Model_ArimaFittingMetrics) GetLogLikelihood() float64 {
  2518  	if x != nil {
  2519  		return x.LogLikelihood
  2520  	}
  2521  	return 0
  2522  }
  2523  
  2524  func (x *Model_ArimaFittingMetrics) GetAic() float64 {
  2525  	if x != nil {
  2526  		return x.Aic
  2527  	}
  2528  	return 0
  2529  }
  2530  
  2531  func (x *Model_ArimaFittingMetrics) GetVariance() float64 {
  2532  	if x != nil {
  2533  		return x.Variance
  2534  	}
  2535  	return 0
  2536  }
  2537  
  2538  // Global explanations containing the top most important features
  2539  // after training.
  2540  type Model_GlobalExplanation struct {
  2541  	state         protoimpl.MessageState
  2542  	sizeCache     protoimpl.SizeCache
  2543  	unknownFields protoimpl.UnknownFields
  2544  
  2545  	// A list of the top global explanations. Sorted by absolute value of
  2546  	// attribution in descending order.
  2547  	Explanations []*Model_GlobalExplanation_Explanation `protobuf:"bytes,1,rep,name=explanations,proto3" json:"explanations,omitempty"`
  2548  	// Class label for this set of global explanations. Will be empty/null for
  2549  	// binary logistic and linear regression models. Sorted alphabetically in
  2550  	// descending order.
  2551  	ClassLabel string `protobuf:"bytes,2,opt,name=class_label,json=classLabel,proto3" json:"class_label,omitempty"`
  2552  }
  2553  
  2554  func (x *Model_GlobalExplanation) Reset() {
  2555  	*x = Model_GlobalExplanation{}
  2556  	if protoimpl.UnsafeEnabled {
  2557  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[19]
  2558  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2559  		ms.StoreMessageInfo(mi)
  2560  	}
  2561  }
  2562  
  2563  func (x *Model_GlobalExplanation) String() string {
  2564  	return protoimpl.X.MessageStringOf(x)
  2565  }
  2566  
  2567  func (*Model_GlobalExplanation) ProtoMessage() {}
  2568  
  2569  func (x *Model_GlobalExplanation) ProtoReflect() protoreflect.Message {
  2570  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[19]
  2571  	if protoimpl.UnsafeEnabled && x != nil {
  2572  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2573  		if ms.LoadMessageInfo() == nil {
  2574  			ms.StoreMessageInfo(mi)
  2575  		}
  2576  		return ms
  2577  	}
  2578  	return mi.MessageOf(x)
  2579  }
  2580  
  2581  // Deprecated: Use Model_GlobalExplanation.ProtoReflect.Descriptor instead.
  2582  func (*Model_GlobalExplanation) Descriptor() ([]byte, []int) {
  2583  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 13}
  2584  }
  2585  
  2586  func (x *Model_GlobalExplanation) GetExplanations() []*Model_GlobalExplanation_Explanation {
  2587  	if x != nil {
  2588  		return x.Explanations
  2589  	}
  2590  	return nil
  2591  }
  2592  
  2593  func (x *Model_GlobalExplanation) GetClassLabel() string {
  2594  	if x != nil {
  2595  		return x.ClassLabel
  2596  	}
  2597  	return ""
  2598  }
  2599  
  2600  // Information about a single training query run for the model.
  2601  type Model_TrainingRun struct {
  2602  	state         protoimpl.MessageState
  2603  	sizeCache     protoimpl.SizeCache
  2604  	unknownFields protoimpl.UnknownFields
  2605  
  2606  	// Options that were used for this training run, includes
  2607  	// user specified and default options that were used.
  2608  	TrainingOptions *Model_TrainingRun_TrainingOptions `protobuf:"bytes,1,opt,name=training_options,json=trainingOptions,proto3" json:"training_options,omitempty"`
  2609  	// The start time of this training run.
  2610  	StartTime *timestamppb.Timestamp `protobuf:"bytes,8,opt,name=start_time,json=startTime,proto3" json:"start_time,omitempty"`
  2611  	// Output of each iteration run, results.size() <= max_iterations.
  2612  	Results []*Model_TrainingRun_IterationResult `protobuf:"bytes,6,rep,name=results,proto3" json:"results,omitempty"`
  2613  	// The evaluation metrics over training/eval data that were computed at the
  2614  	// end of training.
  2615  	EvaluationMetrics *Model_EvaluationMetrics `protobuf:"bytes,7,opt,name=evaluation_metrics,json=evaluationMetrics,proto3" json:"evaluation_metrics,omitempty"`
  2616  	// Data split result of the training run. Only set when the input data is
  2617  	// actually split.
  2618  	DataSplitResult *Model_DataSplitResult `protobuf:"bytes,9,opt,name=data_split_result,json=dataSplitResult,proto3" json:"data_split_result,omitempty"`
  2619  	// Global explanations for important features of the model. For multi-class
  2620  	// models, there is one entry for each label class. For other models, there
  2621  	// is only one entry in the list.
  2622  	GlobalExplanations []*Model_GlobalExplanation `protobuf:"bytes,10,rep,name=global_explanations,json=globalExplanations,proto3" json:"global_explanations,omitempty"`
  2623  }
  2624  
  2625  func (x *Model_TrainingRun) Reset() {
  2626  	*x = Model_TrainingRun{}
  2627  	if protoimpl.UnsafeEnabled {
  2628  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[20]
  2629  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2630  		ms.StoreMessageInfo(mi)
  2631  	}
  2632  }
  2633  
  2634  func (x *Model_TrainingRun) String() string {
  2635  	return protoimpl.X.MessageStringOf(x)
  2636  }
  2637  
  2638  func (*Model_TrainingRun) ProtoMessage() {}
  2639  
  2640  func (x *Model_TrainingRun) ProtoReflect() protoreflect.Message {
  2641  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[20]
  2642  	if protoimpl.UnsafeEnabled && x != nil {
  2643  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2644  		if ms.LoadMessageInfo() == nil {
  2645  			ms.StoreMessageInfo(mi)
  2646  		}
  2647  		return ms
  2648  	}
  2649  	return mi.MessageOf(x)
  2650  }
  2651  
  2652  // Deprecated: Use Model_TrainingRun.ProtoReflect.Descriptor instead.
  2653  func (*Model_TrainingRun) Descriptor() ([]byte, []int) {
  2654  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 14}
  2655  }
  2656  
  2657  func (x *Model_TrainingRun) GetTrainingOptions() *Model_TrainingRun_TrainingOptions {
  2658  	if x != nil {
  2659  		return x.TrainingOptions
  2660  	}
  2661  	return nil
  2662  }
  2663  
  2664  func (x *Model_TrainingRun) GetStartTime() *timestamppb.Timestamp {
  2665  	if x != nil {
  2666  		return x.StartTime
  2667  	}
  2668  	return nil
  2669  }
  2670  
  2671  func (x *Model_TrainingRun) GetResults() []*Model_TrainingRun_IterationResult {
  2672  	if x != nil {
  2673  		return x.Results
  2674  	}
  2675  	return nil
  2676  }
  2677  
  2678  func (x *Model_TrainingRun) GetEvaluationMetrics() *Model_EvaluationMetrics {
  2679  	if x != nil {
  2680  		return x.EvaluationMetrics
  2681  	}
  2682  	return nil
  2683  }
  2684  
  2685  func (x *Model_TrainingRun) GetDataSplitResult() *Model_DataSplitResult {
  2686  	if x != nil {
  2687  		return x.DataSplitResult
  2688  	}
  2689  	return nil
  2690  }
  2691  
  2692  func (x *Model_TrainingRun) GetGlobalExplanations() []*Model_GlobalExplanation {
  2693  	if x != nil {
  2694  		return x.GlobalExplanations
  2695  	}
  2696  	return nil
  2697  }
  2698  
  2699  // Confusion matrix for binary classification models.
  2700  type Model_BinaryClassificationMetrics_BinaryConfusionMatrix struct {
  2701  	state         protoimpl.MessageState
  2702  	sizeCache     protoimpl.SizeCache
  2703  	unknownFields protoimpl.UnknownFields
  2704  
  2705  	// Threshold value used when computing each of the following metric.
  2706  	PositiveClassThreshold *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=positive_class_threshold,json=positiveClassThreshold,proto3" json:"positive_class_threshold,omitempty"`
  2707  	// Number of true samples predicted as true.
  2708  	TruePositives *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=true_positives,json=truePositives,proto3" json:"true_positives,omitempty"`
  2709  	// Number of false samples predicted as true.
  2710  	FalsePositives *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=false_positives,json=falsePositives,proto3" json:"false_positives,omitempty"`
  2711  	// Number of true samples predicted as false.
  2712  	TrueNegatives *wrapperspb.Int64Value `protobuf:"bytes,4,opt,name=true_negatives,json=trueNegatives,proto3" json:"true_negatives,omitempty"`
  2713  	// Number of false samples predicted as false.
  2714  	FalseNegatives *wrapperspb.Int64Value `protobuf:"bytes,5,opt,name=false_negatives,json=falseNegatives,proto3" json:"false_negatives,omitempty"`
  2715  	// The fraction of actual positive predictions that had positive actual
  2716  	// labels.
  2717  	Precision *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=precision,proto3" json:"precision,omitempty"`
  2718  	// The fraction of actual positive labels that were given a positive
  2719  	// prediction.
  2720  	Recall *wrapperspb.DoubleValue `protobuf:"bytes,7,opt,name=recall,proto3" json:"recall,omitempty"`
  2721  	// The equally weighted average of recall and precision.
  2722  	F1Score *wrapperspb.DoubleValue `protobuf:"bytes,8,opt,name=f1_score,json=f1Score,proto3" json:"f1_score,omitempty"`
  2723  	// The fraction of predictions given the correct label.
  2724  	Accuracy *wrapperspb.DoubleValue `protobuf:"bytes,9,opt,name=accuracy,proto3" json:"accuracy,omitempty"`
  2725  }
  2726  
  2727  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Reset() {
  2728  	*x = Model_BinaryClassificationMetrics_BinaryConfusionMatrix{}
  2729  	if protoimpl.UnsafeEnabled {
  2730  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[22]
  2731  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2732  		ms.StoreMessageInfo(mi)
  2733  	}
  2734  }
  2735  
  2736  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) String() string {
  2737  	return protoimpl.X.MessageStringOf(x)
  2738  }
  2739  
  2740  func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoMessage() {}
  2741  
  2742  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) ProtoReflect() protoreflect.Message {
  2743  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[22]
  2744  	if protoimpl.UnsafeEnabled && x != nil {
  2745  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2746  		if ms.LoadMessageInfo() == nil {
  2747  			ms.StoreMessageInfo(mi)
  2748  		}
  2749  		return ms
  2750  	}
  2751  	return mi.MessageOf(x)
  2752  }
  2753  
  2754  // Deprecated: Use Model_BinaryClassificationMetrics_BinaryConfusionMatrix.ProtoReflect.Descriptor instead.
  2755  func (*Model_BinaryClassificationMetrics_BinaryConfusionMatrix) Descriptor() ([]byte, []int) {
  2756  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 4, 0}
  2757  }
  2758  
  2759  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPositiveClassThreshold() *wrapperspb.DoubleValue {
  2760  	if x != nil {
  2761  		return x.PositiveClassThreshold
  2762  	}
  2763  	return nil
  2764  }
  2765  
  2766  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTruePositives() *wrapperspb.Int64Value {
  2767  	if x != nil {
  2768  		return x.TruePositives
  2769  	}
  2770  	return nil
  2771  }
  2772  
  2773  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalsePositives() *wrapperspb.Int64Value {
  2774  	if x != nil {
  2775  		return x.FalsePositives
  2776  	}
  2777  	return nil
  2778  }
  2779  
  2780  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetTrueNegatives() *wrapperspb.Int64Value {
  2781  	if x != nil {
  2782  		return x.TrueNegatives
  2783  	}
  2784  	return nil
  2785  }
  2786  
  2787  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetFalseNegatives() *wrapperspb.Int64Value {
  2788  	if x != nil {
  2789  		return x.FalseNegatives
  2790  	}
  2791  	return nil
  2792  }
  2793  
  2794  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetPrecision() *wrapperspb.DoubleValue {
  2795  	if x != nil {
  2796  		return x.Precision
  2797  	}
  2798  	return nil
  2799  }
  2800  
  2801  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetRecall() *wrapperspb.DoubleValue {
  2802  	if x != nil {
  2803  		return x.Recall
  2804  	}
  2805  	return nil
  2806  }
  2807  
  2808  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetF1Score() *wrapperspb.DoubleValue {
  2809  	if x != nil {
  2810  		return x.F1Score
  2811  	}
  2812  	return nil
  2813  }
  2814  
  2815  func (x *Model_BinaryClassificationMetrics_BinaryConfusionMatrix) GetAccuracy() *wrapperspb.DoubleValue {
  2816  	if x != nil {
  2817  		return x.Accuracy
  2818  	}
  2819  	return nil
  2820  }
  2821  
  2822  // Confusion matrix for multi-class classification models.
  2823  type Model_MultiClassClassificationMetrics_ConfusionMatrix struct {
  2824  	state         protoimpl.MessageState
  2825  	sizeCache     protoimpl.SizeCache
  2826  	unknownFields protoimpl.UnknownFields
  2827  
  2828  	// Confidence threshold used when computing the entries of the
  2829  	// confusion matrix.
  2830  	ConfidenceThreshold *wrapperspb.DoubleValue `protobuf:"bytes,1,opt,name=confidence_threshold,json=confidenceThreshold,proto3" json:"confidence_threshold,omitempty"`
  2831  	// One row per actual label.
  2832  	Rows []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row `protobuf:"bytes,2,rep,name=rows,proto3" json:"rows,omitempty"`
  2833  }
  2834  
  2835  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) Reset() {
  2836  	*x = Model_MultiClassClassificationMetrics_ConfusionMatrix{}
  2837  	if protoimpl.UnsafeEnabled {
  2838  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[23]
  2839  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2840  		ms.StoreMessageInfo(mi)
  2841  	}
  2842  }
  2843  
  2844  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) String() string {
  2845  	return protoimpl.X.MessageStringOf(x)
  2846  }
  2847  
  2848  func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoMessage() {}
  2849  
  2850  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) ProtoReflect() protoreflect.Message {
  2851  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[23]
  2852  	if protoimpl.UnsafeEnabled && x != nil {
  2853  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2854  		if ms.LoadMessageInfo() == nil {
  2855  			ms.StoreMessageInfo(mi)
  2856  		}
  2857  		return ms
  2858  	}
  2859  	return mi.MessageOf(x)
  2860  }
  2861  
  2862  // Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix.ProtoReflect.Descriptor instead.
  2863  func (*Model_MultiClassClassificationMetrics_ConfusionMatrix) Descriptor() ([]byte, []int) {
  2864  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 5, 0}
  2865  }
  2866  
  2867  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) GetConfidenceThreshold() *wrapperspb.DoubleValue {
  2868  	if x != nil {
  2869  		return x.ConfidenceThreshold
  2870  	}
  2871  	return nil
  2872  }
  2873  
  2874  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix) GetRows() []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row {
  2875  	if x != nil {
  2876  		return x.Rows
  2877  	}
  2878  	return nil
  2879  }
  2880  
  2881  // A single entry in the confusion matrix.
  2882  type Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry struct {
  2883  	state         protoimpl.MessageState
  2884  	sizeCache     protoimpl.SizeCache
  2885  	unknownFields protoimpl.UnknownFields
  2886  
  2887  	// The predicted label. For confidence_threshold > 0, we will
  2888  	// also add an entry indicating the number of items under the
  2889  	// confidence threshold.
  2890  	PredictedLabel string `protobuf:"bytes,1,opt,name=predicted_label,json=predictedLabel,proto3" json:"predicted_label,omitempty"`
  2891  	// Number of items being predicted as this label.
  2892  	ItemCount *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=item_count,json=itemCount,proto3" json:"item_count,omitempty"`
  2893  }
  2894  
  2895  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Reset() {
  2896  	*x = Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry{}
  2897  	if protoimpl.UnsafeEnabled {
  2898  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[24]
  2899  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2900  		ms.StoreMessageInfo(mi)
  2901  	}
  2902  }
  2903  
  2904  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) String() string {
  2905  	return protoimpl.X.MessageStringOf(x)
  2906  }
  2907  
  2908  func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoMessage() {}
  2909  
  2910  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) ProtoReflect() protoreflect.Message {
  2911  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[24]
  2912  	if protoimpl.UnsafeEnabled && x != nil {
  2913  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2914  		if ms.LoadMessageInfo() == nil {
  2915  			ms.StoreMessageInfo(mi)
  2916  		}
  2917  		return ms
  2918  	}
  2919  	return mi.MessageOf(x)
  2920  }
  2921  
  2922  // Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry.ProtoReflect.Descriptor instead.
  2923  func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) Descriptor() ([]byte, []int) {
  2924  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 5, 0, 0}
  2925  }
  2926  
  2927  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetPredictedLabel() string {
  2928  	if x != nil {
  2929  		return x.PredictedLabel
  2930  	}
  2931  	return ""
  2932  }
  2933  
  2934  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry) GetItemCount() *wrapperspb.Int64Value {
  2935  	if x != nil {
  2936  		return x.ItemCount
  2937  	}
  2938  	return nil
  2939  }
  2940  
  2941  // A single row in the confusion matrix.
  2942  type Model_MultiClassClassificationMetrics_ConfusionMatrix_Row struct {
  2943  	state         protoimpl.MessageState
  2944  	sizeCache     protoimpl.SizeCache
  2945  	unknownFields protoimpl.UnknownFields
  2946  
  2947  	// The original label of this row.
  2948  	ActualLabel string `protobuf:"bytes,1,opt,name=actual_label,json=actualLabel,proto3" json:"actual_label,omitempty"`
  2949  	// Info describing predicted label distribution.
  2950  	Entries []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry `protobuf:"bytes,2,rep,name=entries,proto3" json:"entries,omitempty"`
  2951  }
  2952  
  2953  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Reset() {
  2954  	*x = Model_MultiClassClassificationMetrics_ConfusionMatrix_Row{}
  2955  	if protoimpl.UnsafeEnabled {
  2956  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[25]
  2957  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2958  		ms.StoreMessageInfo(mi)
  2959  	}
  2960  }
  2961  
  2962  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) String() string {
  2963  	return protoimpl.X.MessageStringOf(x)
  2964  }
  2965  
  2966  func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoMessage() {}
  2967  
  2968  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) ProtoReflect() protoreflect.Message {
  2969  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[25]
  2970  	if protoimpl.UnsafeEnabled && x != nil {
  2971  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  2972  		if ms.LoadMessageInfo() == nil {
  2973  			ms.StoreMessageInfo(mi)
  2974  		}
  2975  		return ms
  2976  	}
  2977  	return mi.MessageOf(x)
  2978  }
  2979  
  2980  // Deprecated: Use Model_MultiClassClassificationMetrics_ConfusionMatrix_Row.ProtoReflect.Descriptor instead.
  2981  func (*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) Descriptor() ([]byte, []int) {
  2982  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 5, 0, 1}
  2983  }
  2984  
  2985  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetActualLabel() string {
  2986  	if x != nil {
  2987  		return x.ActualLabel
  2988  	}
  2989  	return ""
  2990  }
  2991  
  2992  func (x *Model_MultiClassClassificationMetrics_ConfusionMatrix_Row) GetEntries() []*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry {
  2993  	if x != nil {
  2994  		return x.Entries
  2995  	}
  2996  	return nil
  2997  }
  2998  
  2999  // Message containing the information about one cluster.
  3000  type Model_ClusteringMetrics_Cluster struct {
  3001  	state         protoimpl.MessageState
  3002  	sizeCache     protoimpl.SizeCache
  3003  	unknownFields protoimpl.UnknownFields
  3004  
  3005  	// Centroid id.
  3006  	CentroidId int64 `protobuf:"varint,1,opt,name=centroid_id,json=centroidId,proto3" json:"centroid_id,omitempty"`
  3007  	// Values of highly variant features for this cluster.
  3008  	FeatureValues []*Model_ClusteringMetrics_Cluster_FeatureValue `protobuf:"bytes,2,rep,name=feature_values,json=featureValues,proto3" json:"feature_values,omitempty"`
  3009  	// Count of training data rows that were assigned to this cluster.
  3010  	Count *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=count,proto3" json:"count,omitempty"`
  3011  }
  3012  
  3013  func (x *Model_ClusteringMetrics_Cluster) Reset() {
  3014  	*x = Model_ClusteringMetrics_Cluster{}
  3015  	if protoimpl.UnsafeEnabled {
  3016  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[26]
  3017  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3018  		ms.StoreMessageInfo(mi)
  3019  	}
  3020  }
  3021  
  3022  func (x *Model_ClusteringMetrics_Cluster) String() string {
  3023  	return protoimpl.X.MessageStringOf(x)
  3024  }
  3025  
  3026  func (*Model_ClusteringMetrics_Cluster) ProtoMessage() {}
  3027  
  3028  func (x *Model_ClusteringMetrics_Cluster) ProtoReflect() protoreflect.Message {
  3029  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[26]
  3030  	if protoimpl.UnsafeEnabled && x != nil {
  3031  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3032  		if ms.LoadMessageInfo() == nil {
  3033  			ms.StoreMessageInfo(mi)
  3034  		}
  3035  		return ms
  3036  	}
  3037  	return mi.MessageOf(x)
  3038  }
  3039  
  3040  // Deprecated: Use Model_ClusteringMetrics_Cluster.ProtoReflect.Descriptor instead.
  3041  func (*Model_ClusteringMetrics_Cluster) Descriptor() ([]byte, []int) {
  3042  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 6, 0}
  3043  }
  3044  
  3045  func (x *Model_ClusteringMetrics_Cluster) GetCentroidId() int64 {
  3046  	if x != nil {
  3047  		return x.CentroidId
  3048  	}
  3049  	return 0
  3050  }
  3051  
  3052  func (x *Model_ClusteringMetrics_Cluster) GetFeatureValues() []*Model_ClusteringMetrics_Cluster_FeatureValue {
  3053  	if x != nil {
  3054  		return x.FeatureValues
  3055  	}
  3056  	return nil
  3057  }
  3058  
  3059  func (x *Model_ClusteringMetrics_Cluster) GetCount() *wrapperspb.Int64Value {
  3060  	if x != nil {
  3061  		return x.Count
  3062  	}
  3063  	return nil
  3064  }
  3065  
  3066  // Representative value of a single feature within the cluster.
  3067  type Model_ClusteringMetrics_Cluster_FeatureValue struct {
  3068  	state         protoimpl.MessageState
  3069  	sizeCache     protoimpl.SizeCache
  3070  	unknownFields protoimpl.UnknownFields
  3071  
  3072  	// The feature column name.
  3073  	FeatureColumn string `protobuf:"bytes,1,opt,name=feature_column,json=featureColumn,proto3" json:"feature_column,omitempty"`
  3074  	// Types that are assignable to Value:
  3075  	//	*Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue
  3076  	//	*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_
  3077  	Value isModel_ClusteringMetrics_Cluster_FeatureValue_Value `protobuf_oneof:"value"`
  3078  }
  3079  
  3080  func (x *Model_ClusteringMetrics_Cluster_FeatureValue) Reset() {
  3081  	*x = Model_ClusteringMetrics_Cluster_FeatureValue{}
  3082  	if protoimpl.UnsafeEnabled {
  3083  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[27]
  3084  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3085  		ms.StoreMessageInfo(mi)
  3086  	}
  3087  }
  3088  
  3089  func (x *Model_ClusteringMetrics_Cluster_FeatureValue) String() string {
  3090  	return protoimpl.X.MessageStringOf(x)
  3091  }
  3092  
  3093  func (*Model_ClusteringMetrics_Cluster_FeatureValue) ProtoMessage() {}
  3094  
  3095  func (x *Model_ClusteringMetrics_Cluster_FeatureValue) ProtoReflect() protoreflect.Message {
  3096  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[27]
  3097  	if protoimpl.UnsafeEnabled && x != nil {
  3098  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3099  		if ms.LoadMessageInfo() == nil {
  3100  			ms.StoreMessageInfo(mi)
  3101  		}
  3102  		return ms
  3103  	}
  3104  	return mi.MessageOf(x)
  3105  }
  3106  
  3107  // Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue.ProtoReflect.Descriptor instead.
  3108  func (*Model_ClusteringMetrics_Cluster_FeatureValue) Descriptor() ([]byte, []int) {
  3109  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 6, 0, 0}
  3110  }
  3111  
  3112  func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetFeatureColumn() string {
  3113  	if x != nil {
  3114  		return x.FeatureColumn
  3115  	}
  3116  	return ""
  3117  }
  3118  
  3119  func (m *Model_ClusteringMetrics_Cluster_FeatureValue) GetValue() isModel_ClusteringMetrics_Cluster_FeatureValue_Value {
  3120  	if m != nil {
  3121  		return m.Value
  3122  	}
  3123  	return nil
  3124  }
  3125  
  3126  func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetNumericalValue() *wrapperspb.DoubleValue {
  3127  	if x, ok := x.GetValue().(*Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue); ok {
  3128  		return x.NumericalValue
  3129  	}
  3130  	return nil
  3131  }
  3132  
  3133  func (x *Model_ClusteringMetrics_Cluster_FeatureValue) GetCategoricalValue() *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue {
  3134  	if x, ok := x.GetValue().(*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_); ok {
  3135  		return x.CategoricalValue
  3136  	}
  3137  	return nil
  3138  }
  3139  
  3140  type isModel_ClusteringMetrics_Cluster_FeatureValue_Value interface {
  3141  	isModel_ClusteringMetrics_Cluster_FeatureValue_Value()
  3142  }
  3143  
  3144  type Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue struct {
  3145  	// The numerical feature value. This is the centroid value for this
  3146  	// feature.
  3147  	NumericalValue *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=numerical_value,json=numericalValue,proto3,oneof"`
  3148  }
  3149  
  3150  type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_ struct {
  3151  	// The categorical feature value.
  3152  	CategoricalValue *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue `protobuf:"bytes,3,opt,name=categorical_value,json=categoricalValue,proto3,oneof"`
  3153  }
  3154  
  3155  func (*Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue) isModel_ClusteringMetrics_Cluster_FeatureValue_Value() {
  3156  }
  3157  
  3158  func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_) isModel_ClusteringMetrics_Cluster_FeatureValue_Value() {
  3159  }
  3160  
  3161  // Representative value of a categorical feature.
  3162  type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue struct {
  3163  	state         protoimpl.MessageState
  3164  	sizeCache     protoimpl.SizeCache
  3165  	unknownFields protoimpl.UnknownFields
  3166  
  3167  	// Counts of all categories for the categorical feature. If there are
  3168  	// more than ten categories, we return top ten (by count) and return
  3169  	// one more CategoryCount with category "_OTHER_" and count as
  3170  	// aggregate counts of remaining categories.
  3171  	CategoryCounts []*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount `protobuf:"bytes,1,rep,name=category_counts,json=categoryCounts,proto3" json:"category_counts,omitempty"`
  3172  }
  3173  
  3174  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Reset() {
  3175  	*x = Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue{}
  3176  	if protoimpl.UnsafeEnabled {
  3177  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[28]
  3178  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3179  		ms.StoreMessageInfo(mi)
  3180  	}
  3181  }
  3182  
  3183  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) String() string {
  3184  	return protoimpl.X.MessageStringOf(x)
  3185  }
  3186  
  3187  func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoMessage() {}
  3188  
  3189  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) ProtoReflect() protoreflect.Message {
  3190  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[28]
  3191  	if protoimpl.UnsafeEnabled && x != nil {
  3192  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3193  		if ms.LoadMessageInfo() == nil {
  3194  			ms.StoreMessageInfo(mi)
  3195  		}
  3196  		return ms
  3197  	}
  3198  	return mi.MessageOf(x)
  3199  }
  3200  
  3201  // Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue.ProtoReflect.Descriptor instead.
  3202  func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) Descriptor() ([]byte, []int) {
  3203  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 6, 0, 0, 0}
  3204  }
  3205  
  3206  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue) GetCategoryCounts() []*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount {
  3207  	if x != nil {
  3208  		return x.CategoryCounts
  3209  	}
  3210  	return nil
  3211  }
  3212  
  3213  // Represents the count of a single category within the cluster.
  3214  type Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount struct {
  3215  	state         protoimpl.MessageState
  3216  	sizeCache     protoimpl.SizeCache
  3217  	unknownFields protoimpl.UnknownFields
  3218  
  3219  	// The name of category.
  3220  	Category string `protobuf:"bytes,1,opt,name=category,proto3" json:"category,omitempty"`
  3221  	// The count of training samples matching the category within the
  3222  	// cluster.
  3223  	Count *wrapperspb.Int64Value `protobuf:"bytes,2,opt,name=count,proto3" json:"count,omitempty"`
  3224  }
  3225  
  3226  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Reset() {
  3227  	*x = Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount{}
  3228  	if protoimpl.UnsafeEnabled {
  3229  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[29]
  3230  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3231  		ms.StoreMessageInfo(mi)
  3232  	}
  3233  }
  3234  
  3235  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) String() string {
  3236  	return protoimpl.X.MessageStringOf(x)
  3237  }
  3238  
  3239  func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoMessage() {}
  3240  
  3241  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) ProtoReflect() protoreflect.Message {
  3242  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[29]
  3243  	if protoimpl.UnsafeEnabled && x != nil {
  3244  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3245  		if ms.LoadMessageInfo() == nil {
  3246  			ms.StoreMessageInfo(mi)
  3247  		}
  3248  		return ms
  3249  	}
  3250  	return mi.MessageOf(x)
  3251  }
  3252  
  3253  // Deprecated: Use Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount.ProtoReflect.Descriptor instead.
  3254  func (*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) Descriptor() ([]byte, []int) {
  3255  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 6, 0, 0, 0, 0}
  3256  }
  3257  
  3258  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCategory() string {
  3259  	if x != nil {
  3260  		return x.Category
  3261  	}
  3262  	return ""
  3263  }
  3264  
  3265  func (x *Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount) GetCount() *wrapperspb.Int64Value {
  3266  	if x != nil {
  3267  		return x.Count
  3268  	}
  3269  	return nil
  3270  }
  3271  
  3272  // Model evaluation metrics for a single ARIMA forecasting model.
  3273  type Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics struct {
  3274  	state         protoimpl.MessageState
  3275  	sizeCache     protoimpl.SizeCache
  3276  	unknownFields protoimpl.UnknownFields
  3277  
  3278  	// Non-seasonal order.
  3279  	NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,1,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
  3280  	// Arima fitting metrics.
  3281  	ArimaFittingMetrics *Model_ArimaFittingMetrics `protobuf:"bytes,2,opt,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"`
  3282  	// Is arima model fitted with drift or not. It is always false when d
  3283  	// is not 1.
  3284  	HasDrift bool `protobuf:"varint,3,opt,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"`
  3285  	// The time_series_id value for this time series. It will be one of
  3286  	// the unique values from the time_series_id_column specified during
  3287  	// ARIMA model training. Only present when time_series_id_column
  3288  	// training option was used.
  3289  	TimeSeriesId string `protobuf:"bytes,4,opt,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"`
  3290  	// The tuple of time_series_ids identifying this time series. It will
  3291  	// be one of the unique tuples of values present in the
  3292  	// time_series_id_columns specified during ARIMA model training. Only
  3293  	// present when time_series_id_columns training option was used and
  3294  	// the order of values here are same as the order of
  3295  	// time_series_id_columns.
  3296  	TimeSeriesIds []string `protobuf:"bytes,9,rep,name=time_series_ids,json=timeSeriesIds,proto3" json:"time_series_ids,omitempty"`
  3297  	// Seasonal periods. Repeated because multiple periods are supported
  3298  	// for one time series.
  3299  	SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,5,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
  3300  	// If true, holiday_effect is a part of time series decomposition result.
  3301  	HasHolidayEffect *wrapperspb.BoolValue `protobuf:"bytes,6,opt,name=has_holiday_effect,json=hasHolidayEffect,proto3" json:"has_holiday_effect,omitempty"`
  3302  	// If true, spikes_and_dips is a part of time series decomposition result.
  3303  	HasSpikesAndDips *wrapperspb.BoolValue `protobuf:"bytes,7,opt,name=has_spikes_and_dips,json=hasSpikesAndDips,proto3" json:"has_spikes_and_dips,omitempty"`
  3304  	// If true, step_changes is a part of time series decomposition result.
  3305  	HasStepChanges *wrapperspb.BoolValue `protobuf:"bytes,8,opt,name=has_step_changes,json=hasStepChanges,proto3" json:"has_step_changes,omitempty"`
  3306  }
  3307  
  3308  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Reset() {
  3309  	*x = Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics{}
  3310  	if protoimpl.UnsafeEnabled {
  3311  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[30]
  3312  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3313  		ms.StoreMessageInfo(mi)
  3314  	}
  3315  }
  3316  
  3317  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) String() string {
  3318  	return protoimpl.X.MessageStringOf(x)
  3319  }
  3320  
  3321  func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoMessage() {}
  3322  
  3323  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) ProtoReflect() protoreflect.Message {
  3324  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[30]
  3325  	if protoimpl.UnsafeEnabled && x != nil {
  3326  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3327  		if ms.LoadMessageInfo() == nil {
  3328  			ms.StoreMessageInfo(mi)
  3329  		}
  3330  		return ms
  3331  	}
  3332  	return mi.MessageOf(x)
  3333  }
  3334  
  3335  // Deprecated: Use Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics.ProtoReflect.Descriptor instead.
  3336  func (*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) Descriptor() ([]byte, []int) {
  3337  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 8, 0}
  3338  }
  3339  
  3340  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetNonSeasonalOrder() *Model_ArimaOrder {
  3341  	if x != nil {
  3342  		return x.NonSeasonalOrder
  3343  	}
  3344  	return nil
  3345  }
  3346  
  3347  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetArimaFittingMetrics() *Model_ArimaFittingMetrics {
  3348  	if x != nil {
  3349  		return x.ArimaFittingMetrics
  3350  	}
  3351  	return nil
  3352  }
  3353  
  3354  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasDrift() bool {
  3355  	if x != nil {
  3356  		return x.HasDrift
  3357  	}
  3358  	return false
  3359  }
  3360  
  3361  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetTimeSeriesId() string {
  3362  	if x != nil {
  3363  		return x.TimeSeriesId
  3364  	}
  3365  	return ""
  3366  }
  3367  
  3368  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetTimeSeriesIds() []string {
  3369  	if x != nil {
  3370  		return x.TimeSeriesIds
  3371  	}
  3372  	return nil
  3373  }
  3374  
  3375  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType {
  3376  	if x != nil {
  3377  		return x.SeasonalPeriods
  3378  	}
  3379  	return nil
  3380  }
  3381  
  3382  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasHolidayEffect() *wrapperspb.BoolValue {
  3383  	if x != nil {
  3384  		return x.HasHolidayEffect
  3385  	}
  3386  	return nil
  3387  }
  3388  
  3389  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasSpikesAndDips() *wrapperspb.BoolValue {
  3390  	if x != nil {
  3391  		return x.HasSpikesAndDips
  3392  	}
  3393  	return nil
  3394  }
  3395  
  3396  func (x *Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics) GetHasStepChanges() *wrapperspb.BoolValue {
  3397  	if x != nil {
  3398  		return x.HasStepChanges
  3399  	}
  3400  	return nil
  3401  }
  3402  
  3403  // Explanation for a single feature.
  3404  type Model_GlobalExplanation_Explanation struct {
  3405  	state         protoimpl.MessageState
  3406  	sizeCache     protoimpl.SizeCache
  3407  	unknownFields protoimpl.UnknownFields
  3408  
  3409  	// Full name of the feature. For non-numerical features, will be
  3410  	// formatted like <column_name>.<encoded_feature_name>. Overall size of
  3411  	// feature name will always be truncated to first 120 characters.
  3412  	FeatureName string `protobuf:"bytes,1,opt,name=feature_name,json=featureName,proto3" json:"feature_name,omitempty"`
  3413  	// Attribution of feature.
  3414  	Attribution *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=attribution,proto3" json:"attribution,omitempty"`
  3415  }
  3416  
  3417  func (x *Model_GlobalExplanation_Explanation) Reset() {
  3418  	*x = Model_GlobalExplanation_Explanation{}
  3419  	if protoimpl.UnsafeEnabled {
  3420  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[31]
  3421  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3422  		ms.StoreMessageInfo(mi)
  3423  	}
  3424  }
  3425  
  3426  func (x *Model_GlobalExplanation_Explanation) String() string {
  3427  	return protoimpl.X.MessageStringOf(x)
  3428  }
  3429  
  3430  func (*Model_GlobalExplanation_Explanation) ProtoMessage() {}
  3431  
  3432  func (x *Model_GlobalExplanation_Explanation) ProtoReflect() protoreflect.Message {
  3433  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[31]
  3434  	if protoimpl.UnsafeEnabled && x != nil {
  3435  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3436  		if ms.LoadMessageInfo() == nil {
  3437  			ms.StoreMessageInfo(mi)
  3438  		}
  3439  		return ms
  3440  	}
  3441  	return mi.MessageOf(x)
  3442  }
  3443  
  3444  // Deprecated: Use Model_GlobalExplanation_Explanation.ProtoReflect.Descriptor instead.
  3445  func (*Model_GlobalExplanation_Explanation) Descriptor() ([]byte, []int) {
  3446  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 13, 0}
  3447  }
  3448  
  3449  func (x *Model_GlobalExplanation_Explanation) GetFeatureName() string {
  3450  	if x != nil {
  3451  		return x.FeatureName
  3452  	}
  3453  	return ""
  3454  }
  3455  
  3456  func (x *Model_GlobalExplanation_Explanation) GetAttribution() *wrapperspb.DoubleValue {
  3457  	if x != nil {
  3458  		return x.Attribution
  3459  	}
  3460  	return nil
  3461  }
  3462  
  3463  // Options used in model training.
  3464  type Model_TrainingRun_TrainingOptions struct {
  3465  	state         protoimpl.MessageState
  3466  	sizeCache     protoimpl.SizeCache
  3467  	unknownFields protoimpl.UnknownFields
  3468  
  3469  	// The maximum number of iterations in training. Used only for iterative
  3470  	// training algorithms.
  3471  	MaxIterations int64 `protobuf:"varint,1,opt,name=max_iterations,json=maxIterations,proto3" json:"max_iterations,omitempty"`
  3472  	// Type of loss function used during training run.
  3473  	LossType Model_LossType `protobuf:"varint,2,opt,name=loss_type,json=lossType,proto3,enum=google.cloud.bigquery.v2.Model_LossType" json:"loss_type,omitempty"`
  3474  	// Learning rate in training. Used only for iterative training algorithms.
  3475  	LearnRate float64 `protobuf:"fixed64,3,opt,name=learn_rate,json=learnRate,proto3" json:"learn_rate,omitempty"`
  3476  	// L1 regularization coefficient.
  3477  	L1Regularization *wrapperspb.DoubleValue `protobuf:"bytes,4,opt,name=l1_regularization,json=l1Regularization,proto3" json:"l1_regularization,omitempty"`
  3478  	// L2 regularization coefficient.
  3479  	L2Regularization *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=l2_regularization,json=l2Regularization,proto3" json:"l2_regularization,omitempty"`
  3480  	// When early_stop is true, stops training when accuracy improvement is
  3481  	// less than 'min_relative_progress'. Used only for iterative training
  3482  	// algorithms.
  3483  	MinRelativeProgress *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=min_relative_progress,json=minRelativeProgress,proto3" json:"min_relative_progress,omitempty"`
  3484  	// Whether to train a model from the last checkpoint.
  3485  	WarmStart *wrapperspb.BoolValue `protobuf:"bytes,7,opt,name=warm_start,json=warmStart,proto3" json:"warm_start,omitempty"`
  3486  	// Whether to stop early when the loss doesn't improve significantly
  3487  	// any more (compared to min_relative_progress). Used only for iterative
  3488  	// training algorithms.
  3489  	EarlyStop *wrapperspb.BoolValue `protobuf:"bytes,8,opt,name=early_stop,json=earlyStop,proto3" json:"early_stop,omitempty"`
  3490  	// Name of input label columns in training data.
  3491  	InputLabelColumns []string `protobuf:"bytes,9,rep,name=input_label_columns,json=inputLabelColumns,proto3" json:"input_label_columns,omitempty"`
  3492  	// The data split type for training and evaluation, e.g. RANDOM.
  3493  	DataSplitMethod Model_DataSplitMethod `protobuf:"varint,10,opt,name=data_split_method,json=dataSplitMethod,proto3,enum=google.cloud.bigquery.v2.Model_DataSplitMethod" json:"data_split_method,omitempty"`
  3494  	// The fraction of evaluation data over the whole input data. The rest
  3495  	// of data will be used as training data. The format should be double.
  3496  	// Accurate to two decimal places.
  3497  	// Default value is 0.2.
  3498  	DataSplitEvalFraction float64 `protobuf:"fixed64,11,opt,name=data_split_eval_fraction,json=dataSplitEvalFraction,proto3" json:"data_split_eval_fraction,omitempty"`
  3499  	// The column to split data with. This column won't be used as a
  3500  	// feature.
  3501  	// 1. When data_split_method is CUSTOM, the corresponding column should
  3502  	// be boolean. The rows with true value tag are eval data, and the false
  3503  	// are training data.
  3504  	// 2. When data_split_method is SEQ, the first DATA_SPLIT_EVAL_FRACTION
  3505  	// rows (from smallest to largest) in the corresponding column are used
  3506  	// as training data, and the rest are eval data. It respects the order
  3507  	// in Orderable data types:
  3508  	// https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#data-type-properties
  3509  	DataSplitColumn string `protobuf:"bytes,12,opt,name=data_split_column,json=dataSplitColumn,proto3" json:"data_split_column,omitempty"`
  3510  	// The strategy to determine learn rate for the current iteration.
  3511  	LearnRateStrategy Model_LearnRateStrategy `protobuf:"varint,13,opt,name=learn_rate_strategy,json=learnRateStrategy,proto3,enum=google.cloud.bigquery.v2.Model_LearnRateStrategy" json:"learn_rate_strategy,omitempty"`
  3512  	// Specifies the initial learning rate for the line search learn rate
  3513  	// strategy.
  3514  	InitialLearnRate float64 `protobuf:"fixed64,16,opt,name=initial_learn_rate,json=initialLearnRate,proto3" json:"initial_learn_rate,omitempty"`
  3515  	// Weights associated with each label class, for rebalancing the
  3516  	// training data. Only applicable for classification models.
  3517  	LabelClassWeights map[string]float64 `protobuf:"bytes,17,rep,name=label_class_weights,json=labelClassWeights,proto3" json:"label_class_weights,omitempty" protobuf_key:"bytes,1,opt,name=key,proto3" protobuf_val:"fixed64,2,opt,name=value,proto3"`
  3518  	// User column specified for matrix factorization models.
  3519  	UserColumn string `protobuf:"bytes,18,opt,name=user_column,json=userColumn,proto3" json:"user_column,omitempty"`
  3520  	// Item column specified for matrix factorization models.
  3521  	ItemColumn string `protobuf:"bytes,19,opt,name=item_column,json=itemColumn,proto3" json:"item_column,omitempty"`
  3522  	// Distance type for clustering models.
  3523  	DistanceType Model_DistanceType `protobuf:"varint,20,opt,name=distance_type,json=distanceType,proto3,enum=google.cloud.bigquery.v2.Model_DistanceType" json:"distance_type,omitempty"`
  3524  	// Number of clusters for clustering models.
  3525  	NumClusters int64 `protobuf:"varint,21,opt,name=num_clusters,json=numClusters,proto3" json:"num_clusters,omitempty"`
  3526  	// Google Cloud Storage URI from which the model was imported. Only
  3527  	// applicable for imported models.
  3528  	ModelUri string `protobuf:"bytes,22,opt,name=model_uri,json=modelUri,proto3" json:"model_uri,omitempty"`
  3529  	// Optimization strategy for training linear regression models.
  3530  	OptimizationStrategy Model_OptimizationStrategy `protobuf:"varint,23,opt,name=optimization_strategy,json=optimizationStrategy,proto3,enum=google.cloud.bigquery.v2.Model_OptimizationStrategy" json:"optimization_strategy,omitempty"`
  3531  	// Hidden units for dnn models.
  3532  	HiddenUnits []int64 `protobuf:"varint,24,rep,packed,name=hidden_units,json=hiddenUnits,proto3" json:"hidden_units,omitempty"`
  3533  	// Batch size for dnn models.
  3534  	BatchSize int64 `protobuf:"varint,25,opt,name=batch_size,json=batchSize,proto3" json:"batch_size,omitempty"`
  3535  	// Dropout probability for dnn models.
  3536  	Dropout *wrapperspb.DoubleValue `protobuf:"bytes,26,opt,name=dropout,proto3" json:"dropout,omitempty"`
  3537  	// Maximum depth of a tree for boosted tree models.
  3538  	MaxTreeDepth int64 `protobuf:"varint,27,opt,name=max_tree_depth,json=maxTreeDepth,proto3" json:"max_tree_depth,omitempty"`
  3539  	// Subsample fraction of the training data to grow tree to prevent
  3540  	// overfitting for boosted tree models.
  3541  	Subsample float64 `protobuf:"fixed64,28,opt,name=subsample,proto3" json:"subsample,omitempty"`
  3542  	// Minimum split loss for boosted tree models.
  3543  	MinSplitLoss *wrapperspb.DoubleValue `protobuf:"bytes,29,opt,name=min_split_loss,json=minSplitLoss,proto3" json:"min_split_loss,omitempty"`
  3544  	// Num factors specified for matrix factorization models.
  3545  	NumFactors int64 `protobuf:"varint,30,opt,name=num_factors,json=numFactors,proto3" json:"num_factors,omitempty"`
  3546  	// Feedback type that specifies which algorithm to run for matrix
  3547  	// factorization.
  3548  	FeedbackType Model_FeedbackType `protobuf:"varint,31,opt,name=feedback_type,json=feedbackType,proto3,enum=google.cloud.bigquery.v2.Model_FeedbackType" json:"feedback_type,omitempty"`
  3549  	// Hyperparameter for matrix factoration when implicit feedback type is
  3550  	// specified.
  3551  	WalsAlpha *wrapperspb.DoubleValue `protobuf:"bytes,32,opt,name=wals_alpha,json=walsAlpha,proto3" json:"wals_alpha,omitempty"`
  3552  	// The method used to initialize the centroids for kmeans algorithm.
  3553  	KmeansInitializationMethod Model_KmeansEnums_KmeansInitializationMethod `protobuf:"varint,33,opt,name=kmeans_initialization_method,json=kmeansInitializationMethod,proto3,enum=google.cloud.bigquery.v2.Model_KmeansEnums_KmeansInitializationMethod" json:"kmeans_initialization_method,omitempty"`
  3554  	// The column used to provide the initial centroids for kmeans algorithm
  3555  	// when kmeans_initialization_method is CUSTOM.
  3556  	KmeansInitializationColumn string `protobuf:"bytes,34,opt,name=kmeans_initialization_column,json=kmeansInitializationColumn,proto3" json:"kmeans_initialization_column,omitempty"`
  3557  	// Column to be designated as time series timestamp for ARIMA model.
  3558  	TimeSeriesTimestampColumn string `protobuf:"bytes,35,opt,name=time_series_timestamp_column,json=timeSeriesTimestampColumn,proto3" json:"time_series_timestamp_column,omitempty"`
  3559  	// Column to be designated as time series data for ARIMA model.
  3560  	TimeSeriesDataColumn string `protobuf:"bytes,36,opt,name=time_series_data_column,json=timeSeriesDataColumn,proto3" json:"time_series_data_column,omitempty"`
  3561  	// Whether to enable auto ARIMA or not.
  3562  	AutoArima bool `protobuf:"varint,37,opt,name=auto_arima,json=autoArima,proto3" json:"auto_arima,omitempty"`
  3563  	// A specification of the non-seasonal part of the ARIMA model: the three
  3564  	// components (p, d, q) are the AR order, the degree of differencing, and
  3565  	// the MA order.
  3566  	NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,38,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
  3567  	// The data frequency of a time series.
  3568  	DataFrequency Model_DataFrequency `protobuf:"varint,39,opt,name=data_frequency,json=dataFrequency,proto3,enum=google.cloud.bigquery.v2.Model_DataFrequency" json:"data_frequency,omitempty"`
  3569  	// Include drift when fitting an ARIMA model.
  3570  	IncludeDrift bool `protobuf:"varint,41,opt,name=include_drift,json=includeDrift,proto3" json:"include_drift,omitempty"`
  3571  	// The geographical region based on which the holidays are considered in
  3572  	// time series modeling. If a valid value is specified, then holiday
  3573  	// effects modeling is enabled.
  3574  	HolidayRegion Model_HolidayRegion `protobuf:"varint,42,opt,name=holiday_region,json=holidayRegion,proto3,enum=google.cloud.bigquery.v2.Model_HolidayRegion" json:"holiday_region,omitempty"`
  3575  	// The time series id column that was used during ARIMA model training.
  3576  	TimeSeriesIdColumn string `protobuf:"bytes,43,opt,name=time_series_id_column,json=timeSeriesIdColumn,proto3" json:"time_series_id_column,omitempty"`
  3577  	// The time series id columns that were used during ARIMA model training.
  3578  	TimeSeriesIdColumns []string `protobuf:"bytes,51,rep,name=time_series_id_columns,json=timeSeriesIdColumns,proto3" json:"time_series_id_columns,omitempty"`
  3579  	// The number of periods ahead that need to be forecasted.
  3580  	Horizon int64 `protobuf:"varint,44,opt,name=horizon,proto3" json:"horizon,omitempty"`
  3581  	// Whether to preserve the input structs in output feature names.
  3582  	// Suppose there is a struct A with field b.
  3583  	// When false (default), the output feature name is A_b.
  3584  	// When true, the output feature name is A.b.
  3585  	PreserveInputStructs bool `protobuf:"varint,45,opt,name=preserve_input_structs,json=preserveInputStructs,proto3" json:"preserve_input_structs,omitempty"`
  3586  	// The max value of non-seasonal p and q.
  3587  	AutoArimaMaxOrder int64 `protobuf:"varint,46,opt,name=auto_arima_max_order,json=autoArimaMaxOrder,proto3" json:"auto_arima_max_order,omitempty"`
  3588  	// If true, perform decompose time series and save the results.
  3589  	DecomposeTimeSeries *wrapperspb.BoolValue `protobuf:"bytes,50,opt,name=decompose_time_series,json=decomposeTimeSeries,proto3" json:"decompose_time_series,omitempty"`
  3590  	// If true, clean spikes and dips in the input time series.
  3591  	CleanSpikesAndDips *wrapperspb.BoolValue `protobuf:"bytes,52,opt,name=clean_spikes_and_dips,json=cleanSpikesAndDips,proto3" json:"clean_spikes_and_dips,omitempty"`
  3592  	// If true, detect step changes and make data adjustment in the input time
  3593  	// series.
  3594  	AdjustStepChanges *wrapperspb.BoolValue `protobuf:"bytes,53,opt,name=adjust_step_changes,json=adjustStepChanges,proto3" json:"adjust_step_changes,omitempty"`
  3595  }
  3596  
  3597  func (x *Model_TrainingRun_TrainingOptions) Reset() {
  3598  	*x = Model_TrainingRun_TrainingOptions{}
  3599  	if protoimpl.UnsafeEnabled {
  3600  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[32]
  3601  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3602  		ms.StoreMessageInfo(mi)
  3603  	}
  3604  }
  3605  
  3606  func (x *Model_TrainingRun_TrainingOptions) String() string {
  3607  	return protoimpl.X.MessageStringOf(x)
  3608  }
  3609  
  3610  func (*Model_TrainingRun_TrainingOptions) ProtoMessage() {}
  3611  
  3612  func (x *Model_TrainingRun_TrainingOptions) ProtoReflect() protoreflect.Message {
  3613  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[32]
  3614  	if protoimpl.UnsafeEnabled && x != nil {
  3615  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3616  		if ms.LoadMessageInfo() == nil {
  3617  			ms.StoreMessageInfo(mi)
  3618  		}
  3619  		return ms
  3620  	}
  3621  	return mi.MessageOf(x)
  3622  }
  3623  
  3624  // Deprecated: Use Model_TrainingRun_TrainingOptions.ProtoReflect.Descriptor instead.
  3625  func (*Model_TrainingRun_TrainingOptions) Descriptor() ([]byte, []int) {
  3626  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 14, 0}
  3627  }
  3628  
  3629  func (x *Model_TrainingRun_TrainingOptions) GetMaxIterations() int64 {
  3630  	if x != nil {
  3631  		return x.MaxIterations
  3632  	}
  3633  	return 0
  3634  }
  3635  
  3636  func (x *Model_TrainingRun_TrainingOptions) GetLossType() Model_LossType {
  3637  	if x != nil {
  3638  		return x.LossType
  3639  	}
  3640  	return Model_LOSS_TYPE_UNSPECIFIED
  3641  }
  3642  
  3643  func (x *Model_TrainingRun_TrainingOptions) GetLearnRate() float64 {
  3644  	if x != nil {
  3645  		return x.LearnRate
  3646  	}
  3647  	return 0
  3648  }
  3649  
  3650  func (x *Model_TrainingRun_TrainingOptions) GetL1Regularization() *wrapperspb.DoubleValue {
  3651  	if x != nil {
  3652  		return x.L1Regularization
  3653  	}
  3654  	return nil
  3655  }
  3656  
  3657  func (x *Model_TrainingRun_TrainingOptions) GetL2Regularization() *wrapperspb.DoubleValue {
  3658  	if x != nil {
  3659  		return x.L2Regularization
  3660  	}
  3661  	return nil
  3662  }
  3663  
  3664  func (x *Model_TrainingRun_TrainingOptions) GetMinRelativeProgress() *wrapperspb.DoubleValue {
  3665  	if x != nil {
  3666  		return x.MinRelativeProgress
  3667  	}
  3668  	return nil
  3669  }
  3670  
  3671  func (x *Model_TrainingRun_TrainingOptions) GetWarmStart() *wrapperspb.BoolValue {
  3672  	if x != nil {
  3673  		return x.WarmStart
  3674  	}
  3675  	return nil
  3676  }
  3677  
  3678  func (x *Model_TrainingRun_TrainingOptions) GetEarlyStop() *wrapperspb.BoolValue {
  3679  	if x != nil {
  3680  		return x.EarlyStop
  3681  	}
  3682  	return nil
  3683  }
  3684  
  3685  func (x *Model_TrainingRun_TrainingOptions) GetInputLabelColumns() []string {
  3686  	if x != nil {
  3687  		return x.InputLabelColumns
  3688  	}
  3689  	return nil
  3690  }
  3691  
  3692  func (x *Model_TrainingRun_TrainingOptions) GetDataSplitMethod() Model_DataSplitMethod {
  3693  	if x != nil {
  3694  		return x.DataSplitMethod
  3695  	}
  3696  	return Model_DATA_SPLIT_METHOD_UNSPECIFIED
  3697  }
  3698  
  3699  func (x *Model_TrainingRun_TrainingOptions) GetDataSplitEvalFraction() float64 {
  3700  	if x != nil {
  3701  		return x.DataSplitEvalFraction
  3702  	}
  3703  	return 0
  3704  }
  3705  
  3706  func (x *Model_TrainingRun_TrainingOptions) GetDataSplitColumn() string {
  3707  	if x != nil {
  3708  		return x.DataSplitColumn
  3709  	}
  3710  	return ""
  3711  }
  3712  
  3713  func (x *Model_TrainingRun_TrainingOptions) GetLearnRateStrategy() Model_LearnRateStrategy {
  3714  	if x != nil {
  3715  		return x.LearnRateStrategy
  3716  	}
  3717  	return Model_LEARN_RATE_STRATEGY_UNSPECIFIED
  3718  }
  3719  
  3720  func (x *Model_TrainingRun_TrainingOptions) GetInitialLearnRate() float64 {
  3721  	if x != nil {
  3722  		return x.InitialLearnRate
  3723  	}
  3724  	return 0
  3725  }
  3726  
  3727  func (x *Model_TrainingRun_TrainingOptions) GetLabelClassWeights() map[string]float64 {
  3728  	if x != nil {
  3729  		return x.LabelClassWeights
  3730  	}
  3731  	return nil
  3732  }
  3733  
  3734  func (x *Model_TrainingRun_TrainingOptions) GetUserColumn() string {
  3735  	if x != nil {
  3736  		return x.UserColumn
  3737  	}
  3738  	return ""
  3739  }
  3740  
  3741  func (x *Model_TrainingRun_TrainingOptions) GetItemColumn() string {
  3742  	if x != nil {
  3743  		return x.ItemColumn
  3744  	}
  3745  	return ""
  3746  }
  3747  
  3748  func (x *Model_TrainingRun_TrainingOptions) GetDistanceType() Model_DistanceType {
  3749  	if x != nil {
  3750  		return x.DistanceType
  3751  	}
  3752  	return Model_DISTANCE_TYPE_UNSPECIFIED
  3753  }
  3754  
  3755  func (x *Model_TrainingRun_TrainingOptions) GetNumClusters() int64 {
  3756  	if x != nil {
  3757  		return x.NumClusters
  3758  	}
  3759  	return 0
  3760  }
  3761  
  3762  func (x *Model_TrainingRun_TrainingOptions) GetModelUri() string {
  3763  	if x != nil {
  3764  		return x.ModelUri
  3765  	}
  3766  	return ""
  3767  }
  3768  
  3769  func (x *Model_TrainingRun_TrainingOptions) GetOptimizationStrategy() Model_OptimizationStrategy {
  3770  	if x != nil {
  3771  		return x.OptimizationStrategy
  3772  	}
  3773  	return Model_OPTIMIZATION_STRATEGY_UNSPECIFIED
  3774  }
  3775  
  3776  func (x *Model_TrainingRun_TrainingOptions) GetHiddenUnits() []int64 {
  3777  	if x != nil {
  3778  		return x.HiddenUnits
  3779  	}
  3780  	return nil
  3781  }
  3782  
  3783  func (x *Model_TrainingRun_TrainingOptions) GetBatchSize() int64 {
  3784  	if x != nil {
  3785  		return x.BatchSize
  3786  	}
  3787  	return 0
  3788  }
  3789  
  3790  func (x *Model_TrainingRun_TrainingOptions) GetDropout() *wrapperspb.DoubleValue {
  3791  	if x != nil {
  3792  		return x.Dropout
  3793  	}
  3794  	return nil
  3795  }
  3796  
  3797  func (x *Model_TrainingRun_TrainingOptions) GetMaxTreeDepth() int64 {
  3798  	if x != nil {
  3799  		return x.MaxTreeDepth
  3800  	}
  3801  	return 0
  3802  }
  3803  
  3804  func (x *Model_TrainingRun_TrainingOptions) GetSubsample() float64 {
  3805  	if x != nil {
  3806  		return x.Subsample
  3807  	}
  3808  	return 0
  3809  }
  3810  
  3811  func (x *Model_TrainingRun_TrainingOptions) GetMinSplitLoss() *wrapperspb.DoubleValue {
  3812  	if x != nil {
  3813  		return x.MinSplitLoss
  3814  	}
  3815  	return nil
  3816  }
  3817  
  3818  func (x *Model_TrainingRun_TrainingOptions) GetNumFactors() int64 {
  3819  	if x != nil {
  3820  		return x.NumFactors
  3821  	}
  3822  	return 0
  3823  }
  3824  
  3825  func (x *Model_TrainingRun_TrainingOptions) GetFeedbackType() Model_FeedbackType {
  3826  	if x != nil {
  3827  		return x.FeedbackType
  3828  	}
  3829  	return Model_FEEDBACK_TYPE_UNSPECIFIED
  3830  }
  3831  
  3832  func (x *Model_TrainingRun_TrainingOptions) GetWalsAlpha() *wrapperspb.DoubleValue {
  3833  	if x != nil {
  3834  		return x.WalsAlpha
  3835  	}
  3836  	return nil
  3837  }
  3838  
  3839  func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationMethod() Model_KmeansEnums_KmeansInitializationMethod {
  3840  	if x != nil {
  3841  		return x.KmeansInitializationMethod
  3842  	}
  3843  	return Model_KmeansEnums_KMEANS_INITIALIZATION_METHOD_UNSPECIFIED
  3844  }
  3845  
  3846  func (x *Model_TrainingRun_TrainingOptions) GetKmeansInitializationColumn() string {
  3847  	if x != nil {
  3848  		return x.KmeansInitializationColumn
  3849  	}
  3850  	return ""
  3851  }
  3852  
  3853  func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesTimestampColumn() string {
  3854  	if x != nil {
  3855  		return x.TimeSeriesTimestampColumn
  3856  	}
  3857  	return ""
  3858  }
  3859  
  3860  func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesDataColumn() string {
  3861  	if x != nil {
  3862  		return x.TimeSeriesDataColumn
  3863  	}
  3864  	return ""
  3865  }
  3866  
  3867  func (x *Model_TrainingRun_TrainingOptions) GetAutoArima() bool {
  3868  	if x != nil {
  3869  		return x.AutoArima
  3870  	}
  3871  	return false
  3872  }
  3873  
  3874  func (x *Model_TrainingRun_TrainingOptions) GetNonSeasonalOrder() *Model_ArimaOrder {
  3875  	if x != nil {
  3876  		return x.NonSeasonalOrder
  3877  	}
  3878  	return nil
  3879  }
  3880  
  3881  func (x *Model_TrainingRun_TrainingOptions) GetDataFrequency() Model_DataFrequency {
  3882  	if x != nil {
  3883  		return x.DataFrequency
  3884  	}
  3885  	return Model_DATA_FREQUENCY_UNSPECIFIED
  3886  }
  3887  
  3888  func (x *Model_TrainingRun_TrainingOptions) GetIncludeDrift() bool {
  3889  	if x != nil {
  3890  		return x.IncludeDrift
  3891  	}
  3892  	return false
  3893  }
  3894  
  3895  func (x *Model_TrainingRun_TrainingOptions) GetHolidayRegion() Model_HolidayRegion {
  3896  	if x != nil {
  3897  		return x.HolidayRegion
  3898  	}
  3899  	return Model_HOLIDAY_REGION_UNSPECIFIED
  3900  }
  3901  
  3902  func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesIdColumn() string {
  3903  	if x != nil {
  3904  		return x.TimeSeriesIdColumn
  3905  	}
  3906  	return ""
  3907  }
  3908  
  3909  func (x *Model_TrainingRun_TrainingOptions) GetTimeSeriesIdColumns() []string {
  3910  	if x != nil {
  3911  		return x.TimeSeriesIdColumns
  3912  	}
  3913  	return nil
  3914  }
  3915  
  3916  func (x *Model_TrainingRun_TrainingOptions) GetHorizon() int64 {
  3917  	if x != nil {
  3918  		return x.Horizon
  3919  	}
  3920  	return 0
  3921  }
  3922  
  3923  func (x *Model_TrainingRun_TrainingOptions) GetPreserveInputStructs() bool {
  3924  	if x != nil {
  3925  		return x.PreserveInputStructs
  3926  	}
  3927  	return false
  3928  }
  3929  
  3930  func (x *Model_TrainingRun_TrainingOptions) GetAutoArimaMaxOrder() int64 {
  3931  	if x != nil {
  3932  		return x.AutoArimaMaxOrder
  3933  	}
  3934  	return 0
  3935  }
  3936  
  3937  func (x *Model_TrainingRun_TrainingOptions) GetDecomposeTimeSeries() *wrapperspb.BoolValue {
  3938  	if x != nil {
  3939  		return x.DecomposeTimeSeries
  3940  	}
  3941  	return nil
  3942  }
  3943  
  3944  func (x *Model_TrainingRun_TrainingOptions) GetCleanSpikesAndDips() *wrapperspb.BoolValue {
  3945  	if x != nil {
  3946  		return x.CleanSpikesAndDips
  3947  	}
  3948  	return nil
  3949  }
  3950  
  3951  func (x *Model_TrainingRun_TrainingOptions) GetAdjustStepChanges() *wrapperspb.BoolValue {
  3952  	if x != nil {
  3953  		return x.AdjustStepChanges
  3954  	}
  3955  	return nil
  3956  }
  3957  
  3958  // Information about a single iteration of the training run.
  3959  type Model_TrainingRun_IterationResult struct {
  3960  	state         protoimpl.MessageState
  3961  	sizeCache     protoimpl.SizeCache
  3962  	unknownFields protoimpl.UnknownFields
  3963  
  3964  	// Index of the iteration, 0 based.
  3965  	Index *wrapperspb.Int32Value `protobuf:"bytes,1,opt,name=index,proto3" json:"index,omitempty"`
  3966  	// Time taken to run the iteration in milliseconds.
  3967  	DurationMs *wrapperspb.Int64Value `protobuf:"bytes,4,opt,name=duration_ms,json=durationMs,proto3" json:"duration_ms,omitempty"`
  3968  	// Loss computed on the training data at the end of iteration.
  3969  	TrainingLoss *wrapperspb.DoubleValue `protobuf:"bytes,5,opt,name=training_loss,json=trainingLoss,proto3" json:"training_loss,omitempty"`
  3970  	// Loss computed on the eval data at the end of iteration.
  3971  	EvalLoss *wrapperspb.DoubleValue `protobuf:"bytes,6,opt,name=eval_loss,json=evalLoss,proto3" json:"eval_loss,omitempty"`
  3972  	// Learn rate used for this iteration.
  3973  	LearnRate float64 `protobuf:"fixed64,7,opt,name=learn_rate,json=learnRate,proto3" json:"learn_rate,omitempty"`
  3974  	// Information about top clusters for clustering models.
  3975  	ClusterInfos []*Model_TrainingRun_IterationResult_ClusterInfo `protobuf:"bytes,8,rep,name=cluster_infos,json=clusterInfos,proto3" json:"cluster_infos,omitempty"`
  3976  	ArimaResult  *Model_TrainingRun_IterationResult_ArimaResult   `protobuf:"bytes,9,opt,name=arima_result,json=arimaResult,proto3" json:"arima_result,omitempty"`
  3977  }
  3978  
  3979  func (x *Model_TrainingRun_IterationResult) Reset() {
  3980  	*x = Model_TrainingRun_IterationResult{}
  3981  	if protoimpl.UnsafeEnabled {
  3982  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[33]
  3983  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3984  		ms.StoreMessageInfo(mi)
  3985  	}
  3986  }
  3987  
  3988  func (x *Model_TrainingRun_IterationResult) String() string {
  3989  	return protoimpl.X.MessageStringOf(x)
  3990  }
  3991  
  3992  func (*Model_TrainingRun_IterationResult) ProtoMessage() {}
  3993  
  3994  func (x *Model_TrainingRun_IterationResult) ProtoReflect() protoreflect.Message {
  3995  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[33]
  3996  	if protoimpl.UnsafeEnabled && x != nil {
  3997  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  3998  		if ms.LoadMessageInfo() == nil {
  3999  			ms.StoreMessageInfo(mi)
  4000  		}
  4001  		return ms
  4002  	}
  4003  	return mi.MessageOf(x)
  4004  }
  4005  
  4006  // Deprecated: Use Model_TrainingRun_IterationResult.ProtoReflect.Descriptor instead.
  4007  func (*Model_TrainingRun_IterationResult) Descriptor() ([]byte, []int) {
  4008  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 14, 1}
  4009  }
  4010  
  4011  func (x *Model_TrainingRun_IterationResult) GetIndex() *wrapperspb.Int32Value {
  4012  	if x != nil {
  4013  		return x.Index
  4014  	}
  4015  	return nil
  4016  }
  4017  
  4018  func (x *Model_TrainingRun_IterationResult) GetDurationMs() *wrapperspb.Int64Value {
  4019  	if x != nil {
  4020  		return x.DurationMs
  4021  	}
  4022  	return nil
  4023  }
  4024  
  4025  func (x *Model_TrainingRun_IterationResult) GetTrainingLoss() *wrapperspb.DoubleValue {
  4026  	if x != nil {
  4027  		return x.TrainingLoss
  4028  	}
  4029  	return nil
  4030  }
  4031  
  4032  func (x *Model_TrainingRun_IterationResult) GetEvalLoss() *wrapperspb.DoubleValue {
  4033  	if x != nil {
  4034  		return x.EvalLoss
  4035  	}
  4036  	return nil
  4037  }
  4038  
  4039  func (x *Model_TrainingRun_IterationResult) GetLearnRate() float64 {
  4040  	if x != nil {
  4041  		return x.LearnRate
  4042  	}
  4043  	return 0
  4044  }
  4045  
  4046  func (x *Model_TrainingRun_IterationResult) GetClusterInfos() []*Model_TrainingRun_IterationResult_ClusterInfo {
  4047  	if x != nil {
  4048  		return x.ClusterInfos
  4049  	}
  4050  	return nil
  4051  }
  4052  
  4053  func (x *Model_TrainingRun_IterationResult) GetArimaResult() *Model_TrainingRun_IterationResult_ArimaResult {
  4054  	if x != nil {
  4055  		return x.ArimaResult
  4056  	}
  4057  	return nil
  4058  }
  4059  
  4060  // Information about a single cluster for clustering model.
  4061  type Model_TrainingRun_IterationResult_ClusterInfo struct {
  4062  	state         protoimpl.MessageState
  4063  	sizeCache     protoimpl.SizeCache
  4064  	unknownFields protoimpl.UnknownFields
  4065  
  4066  	// Centroid id.
  4067  	CentroidId int64 `protobuf:"varint,1,opt,name=centroid_id,json=centroidId,proto3" json:"centroid_id,omitempty"`
  4068  	// Cluster radius, the average distance from centroid
  4069  	// to each point assigned to the cluster.
  4070  	ClusterRadius *wrapperspb.DoubleValue `protobuf:"bytes,2,opt,name=cluster_radius,json=clusterRadius,proto3" json:"cluster_radius,omitempty"`
  4071  	// Cluster size, the total number of points assigned to the cluster.
  4072  	ClusterSize *wrapperspb.Int64Value `protobuf:"bytes,3,opt,name=cluster_size,json=clusterSize,proto3" json:"cluster_size,omitempty"`
  4073  }
  4074  
  4075  func (x *Model_TrainingRun_IterationResult_ClusterInfo) Reset() {
  4076  	*x = Model_TrainingRun_IterationResult_ClusterInfo{}
  4077  	if protoimpl.UnsafeEnabled {
  4078  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[35]
  4079  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4080  		ms.StoreMessageInfo(mi)
  4081  	}
  4082  }
  4083  
  4084  func (x *Model_TrainingRun_IterationResult_ClusterInfo) String() string {
  4085  	return protoimpl.X.MessageStringOf(x)
  4086  }
  4087  
  4088  func (*Model_TrainingRun_IterationResult_ClusterInfo) ProtoMessage() {}
  4089  
  4090  func (x *Model_TrainingRun_IterationResult_ClusterInfo) ProtoReflect() protoreflect.Message {
  4091  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[35]
  4092  	if protoimpl.UnsafeEnabled && x != nil {
  4093  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4094  		if ms.LoadMessageInfo() == nil {
  4095  			ms.StoreMessageInfo(mi)
  4096  		}
  4097  		return ms
  4098  	}
  4099  	return mi.MessageOf(x)
  4100  }
  4101  
  4102  // Deprecated: Use Model_TrainingRun_IterationResult_ClusterInfo.ProtoReflect.Descriptor instead.
  4103  func (*Model_TrainingRun_IterationResult_ClusterInfo) Descriptor() ([]byte, []int) {
  4104  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 14, 1, 0}
  4105  }
  4106  
  4107  func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetCentroidId() int64 {
  4108  	if x != nil {
  4109  		return x.CentroidId
  4110  	}
  4111  	return 0
  4112  }
  4113  
  4114  func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterRadius() *wrapperspb.DoubleValue {
  4115  	if x != nil {
  4116  		return x.ClusterRadius
  4117  	}
  4118  	return nil
  4119  }
  4120  
  4121  func (x *Model_TrainingRun_IterationResult_ClusterInfo) GetClusterSize() *wrapperspb.Int64Value {
  4122  	if x != nil {
  4123  		return x.ClusterSize
  4124  	}
  4125  	return nil
  4126  }
  4127  
  4128  // (Auto-)arima fitting result. Wrap everything in ArimaResult for easier
  4129  // refactoring if we want to use model-specific iteration results.
  4130  type Model_TrainingRun_IterationResult_ArimaResult struct {
  4131  	state         protoimpl.MessageState
  4132  	sizeCache     protoimpl.SizeCache
  4133  	unknownFields protoimpl.UnknownFields
  4134  
  4135  	// This message is repeated because there are multiple arima models
  4136  	// fitted in auto-arima. For non-auto-arima model, its size is one.
  4137  	ArimaModelInfo []*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo `protobuf:"bytes,1,rep,name=arima_model_info,json=arimaModelInfo,proto3" json:"arima_model_info,omitempty"`
  4138  	// Seasonal periods. Repeated because multiple periods are supported for
  4139  	// one time series.
  4140  	SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,2,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
  4141  }
  4142  
  4143  func (x *Model_TrainingRun_IterationResult_ArimaResult) Reset() {
  4144  	*x = Model_TrainingRun_IterationResult_ArimaResult{}
  4145  	if protoimpl.UnsafeEnabled {
  4146  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[36]
  4147  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4148  		ms.StoreMessageInfo(mi)
  4149  	}
  4150  }
  4151  
  4152  func (x *Model_TrainingRun_IterationResult_ArimaResult) String() string {
  4153  	return protoimpl.X.MessageStringOf(x)
  4154  }
  4155  
  4156  func (*Model_TrainingRun_IterationResult_ArimaResult) ProtoMessage() {}
  4157  
  4158  func (x *Model_TrainingRun_IterationResult_ArimaResult) ProtoReflect() protoreflect.Message {
  4159  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[36]
  4160  	if protoimpl.UnsafeEnabled && x != nil {
  4161  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4162  		if ms.LoadMessageInfo() == nil {
  4163  			ms.StoreMessageInfo(mi)
  4164  		}
  4165  		return ms
  4166  	}
  4167  	return mi.MessageOf(x)
  4168  }
  4169  
  4170  // Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult.ProtoReflect.Descriptor instead.
  4171  func (*Model_TrainingRun_IterationResult_ArimaResult) Descriptor() ([]byte, []int) {
  4172  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 14, 1, 1}
  4173  }
  4174  
  4175  func (x *Model_TrainingRun_IterationResult_ArimaResult) GetArimaModelInfo() []*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo {
  4176  	if x != nil {
  4177  		return x.ArimaModelInfo
  4178  	}
  4179  	return nil
  4180  }
  4181  
  4182  func (x *Model_TrainingRun_IterationResult_ArimaResult) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType {
  4183  	if x != nil {
  4184  		return x.SeasonalPeriods
  4185  	}
  4186  	return nil
  4187  }
  4188  
  4189  // Arima coefficients.
  4190  type Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients struct {
  4191  	state         protoimpl.MessageState
  4192  	sizeCache     protoimpl.SizeCache
  4193  	unknownFields protoimpl.UnknownFields
  4194  
  4195  	// Auto-regressive coefficients, an array of double.
  4196  	AutoRegressiveCoefficients []float64 `protobuf:"fixed64,1,rep,packed,name=auto_regressive_coefficients,json=autoRegressiveCoefficients,proto3" json:"auto_regressive_coefficients,omitempty"`
  4197  	// Moving-average coefficients, an array of double.
  4198  	MovingAverageCoefficients []float64 `protobuf:"fixed64,2,rep,packed,name=moving_average_coefficients,json=movingAverageCoefficients,proto3" json:"moving_average_coefficients,omitempty"`
  4199  	// Intercept coefficient, just a double not an array.
  4200  	InterceptCoefficient float64 `protobuf:"fixed64,3,opt,name=intercept_coefficient,json=interceptCoefficient,proto3" json:"intercept_coefficient,omitempty"`
  4201  }
  4202  
  4203  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Reset() {
  4204  	*x = Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients{}
  4205  	if protoimpl.UnsafeEnabled {
  4206  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[37]
  4207  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4208  		ms.StoreMessageInfo(mi)
  4209  	}
  4210  }
  4211  
  4212  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) String() string {
  4213  	return protoimpl.X.MessageStringOf(x)
  4214  }
  4215  
  4216  func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoMessage() {}
  4217  
  4218  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) ProtoReflect() protoreflect.Message {
  4219  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[37]
  4220  	if protoimpl.UnsafeEnabled && x != nil {
  4221  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4222  		if ms.LoadMessageInfo() == nil {
  4223  			ms.StoreMessageInfo(mi)
  4224  		}
  4225  		return ms
  4226  	}
  4227  	return mi.MessageOf(x)
  4228  }
  4229  
  4230  // Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients.ProtoReflect.Descriptor instead.
  4231  func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) Descriptor() ([]byte, []int) {
  4232  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 14, 1, 1, 0}
  4233  }
  4234  
  4235  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetAutoRegressiveCoefficients() []float64 {
  4236  	if x != nil {
  4237  		return x.AutoRegressiveCoefficients
  4238  	}
  4239  	return nil
  4240  }
  4241  
  4242  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetMovingAverageCoefficients() []float64 {
  4243  	if x != nil {
  4244  		return x.MovingAverageCoefficients
  4245  	}
  4246  	return nil
  4247  }
  4248  
  4249  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients) GetInterceptCoefficient() float64 {
  4250  	if x != nil {
  4251  		return x.InterceptCoefficient
  4252  	}
  4253  	return 0
  4254  }
  4255  
  4256  // Arima model information.
  4257  type Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo struct {
  4258  	state         protoimpl.MessageState
  4259  	sizeCache     protoimpl.SizeCache
  4260  	unknownFields protoimpl.UnknownFields
  4261  
  4262  	// Non-seasonal order.
  4263  	NonSeasonalOrder *Model_ArimaOrder `protobuf:"bytes,1,opt,name=non_seasonal_order,json=nonSeasonalOrder,proto3" json:"non_seasonal_order,omitempty"`
  4264  	// Arima coefficients.
  4265  	ArimaCoefficients *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients `protobuf:"bytes,2,opt,name=arima_coefficients,json=arimaCoefficients,proto3" json:"arima_coefficients,omitempty"`
  4266  	// Arima fitting metrics.
  4267  	ArimaFittingMetrics *Model_ArimaFittingMetrics `protobuf:"bytes,3,opt,name=arima_fitting_metrics,json=arimaFittingMetrics,proto3" json:"arima_fitting_metrics,omitempty"`
  4268  	// Whether Arima model fitted with drift or not. It is always false
  4269  	// when d is not 1.
  4270  	HasDrift bool `protobuf:"varint,4,opt,name=has_drift,json=hasDrift,proto3" json:"has_drift,omitempty"`
  4271  	// The time_series_id value for this time series. It will be one of
  4272  	// the unique values from the time_series_id_column specified during
  4273  	// ARIMA model training. Only present when time_series_id_column
  4274  	// training option was used.
  4275  	TimeSeriesId string `protobuf:"bytes,5,opt,name=time_series_id,json=timeSeriesId,proto3" json:"time_series_id,omitempty"`
  4276  	// The tuple of time_series_ids identifying this time series. It will
  4277  	// be one of the unique tuples of values present in the
  4278  	// time_series_id_columns specified during ARIMA model training. Only
  4279  	// present when time_series_id_columns training option was used and
  4280  	// the order of values here are same as the order of
  4281  	// time_series_id_columns.
  4282  	TimeSeriesIds []string `protobuf:"bytes,10,rep,name=time_series_ids,json=timeSeriesIds,proto3" json:"time_series_ids,omitempty"`
  4283  	// Seasonal periods. Repeated because multiple periods are supported
  4284  	// for one time series.
  4285  	SeasonalPeriods []Model_SeasonalPeriod_SeasonalPeriodType `protobuf:"varint,6,rep,packed,name=seasonal_periods,json=seasonalPeriods,proto3,enum=google.cloud.bigquery.v2.Model_SeasonalPeriod_SeasonalPeriodType" json:"seasonal_periods,omitempty"`
  4286  	// If true, holiday_effect is a part of time series decomposition
  4287  	// result.
  4288  	HasHolidayEffect *wrapperspb.BoolValue `protobuf:"bytes,7,opt,name=has_holiday_effect,json=hasHolidayEffect,proto3" json:"has_holiday_effect,omitempty"`
  4289  	// If true, spikes_and_dips is a part of time series decomposition
  4290  	// result.
  4291  	HasSpikesAndDips *wrapperspb.BoolValue `protobuf:"bytes,8,opt,name=has_spikes_and_dips,json=hasSpikesAndDips,proto3" json:"has_spikes_and_dips,omitempty"`
  4292  	// If true, step_changes is a part of time series decomposition
  4293  	// result.
  4294  	HasStepChanges *wrapperspb.BoolValue `protobuf:"bytes,9,opt,name=has_step_changes,json=hasStepChanges,proto3" json:"has_step_changes,omitempty"`
  4295  }
  4296  
  4297  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Reset() {
  4298  	*x = Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo{}
  4299  	if protoimpl.UnsafeEnabled {
  4300  		mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[38]
  4301  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4302  		ms.StoreMessageInfo(mi)
  4303  	}
  4304  }
  4305  
  4306  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) String() string {
  4307  	return protoimpl.X.MessageStringOf(x)
  4308  }
  4309  
  4310  func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoMessage() {}
  4311  
  4312  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) ProtoReflect() protoreflect.Message {
  4313  	mi := &file_google_cloud_bigquery_v2_model_proto_msgTypes[38]
  4314  	if protoimpl.UnsafeEnabled && x != nil {
  4315  		ms := protoimpl.X.MessageStateOf(protoimpl.Pointer(x))
  4316  		if ms.LoadMessageInfo() == nil {
  4317  			ms.StoreMessageInfo(mi)
  4318  		}
  4319  		return ms
  4320  	}
  4321  	return mi.MessageOf(x)
  4322  }
  4323  
  4324  // Deprecated: Use Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo.ProtoReflect.Descriptor instead.
  4325  func (*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) Descriptor() ([]byte, []int) {
  4326  	return file_google_cloud_bigquery_v2_model_proto_rawDescGZIP(), []int{0, 14, 1, 1, 1}
  4327  }
  4328  
  4329  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetNonSeasonalOrder() *Model_ArimaOrder {
  4330  	if x != nil {
  4331  		return x.NonSeasonalOrder
  4332  	}
  4333  	return nil
  4334  }
  4335  
  4336  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaCoefficients() *Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients {
  4337  	if x != nil {
  4338  		return x.ArimaCoefficients
  4339  	}
  4340  	return nil
  4341  }
  4342  
  4343  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetArimaFittingMetrics() *Model_ArimaFittingMetrics {
  4344  	if x != nil {
  4345  		return x.ArimaFittingMetrics
  4346  	}
  4347  	return nil
  4348  }
  4349  
  4350  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasDrift() bool {
  4351  	if x != nil {
  4352  		return x.HasDrift
  4353  	}
  4354  	return false
  4355  }
  4356  
  4357  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetTimeSeriesId() string {
  4358  	if x != nil {
  4359  		return x.TimeSeriesId
  4360  	}
  4361  	return ""
  4362  }
  4363  
  4364  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetTimeSeriesIds() []string {
  4365  	if x != nil {
  4366  		return x.TimeSeriesIds
  4367  	}
  4368  	return nil
  4369  }
  4370  
  4371  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetSeasonalPeriods() []Model_SeasonalPeriod_SeasonalPeriodType {
  4372  	if x != nil {
  4373  		return x.SeasonalPeriods
  4374  	}
  4375  	return nil
  4376  }
  4377  
  4378  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasHolidayEffect() *wrapperspb.BoolValue {
  4379  	if x != nil {
  4380  		return x.HasHolidayEffect
  4381  	}
  4382  	return nil
  4383  }
  4384  
  4385  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasSpikesAndDips() *wrapperspb.BoolValue {
  4386  	if x != nil {
  4387  		return x.HasSpikesAndDips
  4388  	}
  4389  	return nil
  4390  }
  4391  
  4392  func (x *Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo) GetHasStepChanges() *wrapperspb.BoolValue {
  4393  	if x != nil {
  4394  		return x.HasStepChanges
  4395  	}
  4396  	return nil
  4397  }
  4398  
  4399  var File_google_cloud_bigquery_v2_model_proto protoreflect.FileDescriptor
  4400  
  4401  var file_google_cloud_bigquery_v2_model_proto_rawDesc = []byte{
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  5491  	0x6f, 0x74, 0x6f, 0x33,
  5492  }
  5493  
  5494  var (
  5495  	file_google_cloud_bigquery_v2_model_proto_rawDescOnce sync.Once
  5496  	file_google_cloud_bigquery_v2_model_proto_rawDescData = file_google_cloud_bigquery_v2_model_proto_rawDesc
  5497  )
  5498  
  5499  func file_google_cloud_bigquery_v2_model_proto_rawDescGZIP() []byte {
  5500  	file_google_cloud_bigquery_v2_model_proto_rawDescOnce.Do(func() {
  5501  		file_google_cloud_bigquery_v2_model_proto_rawDescData = protoimpl.X.CompressGZIP(file_google_cloud_bigquery_v2_model_proto_rawDescData)
  5502  	})
  5503  	return file_google_cloud_bigquery_v2_model_proto_rawDescData
  5504  }
  5505  
  5506  var file_google_cloud_bigquery_v2_model_proto_enumTypes = make([]protoimpl.EnumInfo, 11)
  5507  var file_google_cloud_bigquery_v2_model_proto_msgTypes = make([]protoimpl.MessageInfo, 39)
  5508  var file_google_cloud_bigquery_v2_model_proto_goTypes = []interface{}{
  5509  	(Model_ModelType)(0),                                                  // 0: google.cloud.bigquery.v2.Model.ModelType
  5510  	(Model_LossType)(0),                                                   // 1: google.cloud.bigquery.v2.Model.LossType
  5511  	(Model_DistanceType)(0),                                               // 2: google.cloud.bigquery.v2.Model.DistanceType
  5512  	(Model_DataSplitMethod)(0),                                            // 3: google.cloud.bigquery.v2.Model.DataSplitMethod
  5513  	(Model_DataFrequency)(0),                                              // 4: google.cloud.bigquery.v2.Model.DataFrequency
  5514  	(Model_HolidayRegion)(0),                                              // 5: google.cloud.bigquery.v2.Model.HolidayRegion
  5515  	(Model_LearnRateStrategy)(0),                                          // 6: google.cloud.bigquery.v2.Model.LearnRateStrategy
  5516  	(Model_OptimizationStrategy)(0),                                       // 7: google.cloud.bigquery.v2.Model.OptimizationStrategy
  5517  	(Model_FeedbackType)(0),                                               // 8: google.cloud.bigquery.v2.Model.FeedbackType
  5518  	(Model_SeasonalPeriod_SeasonalPeriodType)(0),                          // 9: google.cloud.bigquery.v2.Model.SeasonalPeriod.SeasonalPeriodType
  5519  	(Model_KmeansEnums_KmeansInitializationMethod)(0),                     // 10: google.cloud.bigquery.v2.Model.KmeansEnums.KmeansInitializationMethod
  5520  	(*Model)(nil),                                                         // 11: google.cloud.bigquery.v2.Model
  5521  	(*GetModelRequest)(nil),                                               // 12: google.cloud.bigquery.v2.GetModelRequest
  5522  	(*PatchModelRequest)(nil),                                             // 13: google.cloud.bigquery.v2.PatchModelRequest
  5523  	(*DeleteModelRequest)(nil),                                            // 14: google.cloud.bigquery.v2.DeleteModelRequest
  5524  	(*ListModelsRequest)(nil),                                             // 15: google.cloud.bigquery.v2.ListModelsRequest
  5525  	(*ListModelsResponse)(nil),                                            // 16: google.cloud.bigquery.v2.ListModelsResponse
  5526  	(*Model_SeasonalPeriod)(nil),                                          // 17: google.cloud.bigquery.v2.Model.SeasonalPeriod
  5527  	(*Model_KmeansEnums)(nil),                                             // 18: google.cloud.bigquery.v2.Model.KmeansEnums
  5528  	(*Model_RegressionMetrics)(nil),                                       // 19: google.cloud.bigquery.v2.Model.RegressionMetrics
  5529  	(*Model_AggregateClassificationMetrics)(nil),                          // 20: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics
  5530  	(*Model_BinaryClassificationMetrics)(nil),                             // 21: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics
  5531  	(*Model_MultiClassClassificationMetrics)(nil),                         // 22: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics
  5532  	(*Model_ClusteringMetrics)(nil),                                       // 23: google.cloud.bigquery.v2.Model.ClusteringMetrics
  5533  	(*Model_RankingMetrics)(nil),                                          // 24: google.cloud.bigquery.v2.Model.RankingMetrics
  5534  	(*Model_ArimaForecastingMetrics)(nil),                                 // 25: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics
  5535  	(*Model_EvaluationMetrics)(nil),                                       // 26: google.cloud.bigquery.v2.Model.EvaluationMetrics
  5536  	(*Model_DataSplitResult)(nil),                                         // 27: google.cloud.bigquery.v2.Model.DataSplitResult
  5537  	(*Model_ArimaOrder)(nil),                                              // 28: google.cloud.bigquery.v2.Model.ArimaOrder
  5538  	(*Model_ArimaFittingMetrics)(nil),                                     // 29: google.cloud.bigquery.v2.Model.ArimaFittingMetrics
  5539  	(*Model_GlobalExplanation)(nil),                                       // 30: google.cloud.bigquery.v2.Model.GlobalExplanation
  5540  	(*Model_TrainingRun)(nil),                                             // 31: google.cloud.bigquery.v2.Model.TrainingRun
  5541  	nil,                                                                   // 32: google.cloud.bigquery.v2.Model.LabelsEntry
  5542  	(*Model_BinaryClassificationMetrics_BinaryConfusionMatrix)(nil),       // 33: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix
  5543  	(*Model_MultiClassClassificationMetrics_ConfusionMatrix)(nil),         // 34: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix
  5544  	(*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry)(nil),   // 35: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry
  5545  	(*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row)(nil),     // 36: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row
  5546  	(*Model_ClusteringMetrics_Cluster)(nil),                               // 37: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster
  5547  	(*Model_ClusteringMetrics_Cluster_FeatureValue)(nil),                  // 38: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue
  5548  	(*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue)(nil), // 39: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue
  5549  	(*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount)(nil), // 40: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount
  5550  	(*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics)(nil),            // 41: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics
  5551  	(*Model_GlobalExplanation_Explanation)(nil),                                         // 42: google.cloud.bigquery.v2.Model.GlobalExplanation.Explanation
  5552  	(*Model_TrainingRun_TrainingOptions)(nil),                                           // 43: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions
  5553  	(*Model_TrainingRun_IterationResult)(nil),                                           // 44: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult
  5554  	nil, // 45: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry
  5555  	(*Model_TrainingRun_IterationResult_ClusterInfo)(nil),                   // 46: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo
  5556  	(*Model_TrainingRun_IterationResult_ArimaResult)(nil),                   // 47: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult
  5557  	(*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients)(nil), // 48: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients
  5558  	(*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo)(nil),    // 49: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo
  5559  	(*ModelReference)(nil),          // 50: google.cloud.bigquery.v2.ModelReference
  5560  	(*EncryptionConfiguration)(nil), // 51: google.cloud.bigquery.v2.EncryptionConfiguration
  5561  	(*StandardSqlField)(nil),        // 52: google.cloud.bigquery.v2.StandardSqlField
  5562  	(*wrapperspb.UInt32Value)(nil),  // 53: google.protobuf.UInt32Value
  5563  	(*wrapperspb.DoubleValue)(nil),  // 54: google.protobuf.DoubleValue
  5564  	(*TableReference)(nil),          // 55: google.cloud.bigquery.v2.TableReference
  5565  	(*timestamppb.Timestamp)(nil),   // 56: google.protobuf.Timestamp
  5566  	(*wrapperspb.Int64Value)(nil),   // 57: google.protobuf.Int64Value
  5567  	(*wrapperspb.BoolValue)(nil),    // 58: google.protobuf.BoolValue
  5568  	(*wrapperspb.Int32Value)(nil),   // 59: google.protobuf.Int32Value
  5569  	(*emptypb.Empty)(nil),           // 60: google.protobuf.Empty
  5570  }
  5571  var file_google_cloud_bigquery_v2_model_proto_depIdxs = []int32{
  5572  	50,  // 0: google.cloud.bigquery.v2.Model.model_reference:type_name -> google.cloud.bigquery.v2.ModelReference
  5573  	32,  // 1: google.cloud.bigquery.v2.Model.labels:type_name -> google.cloud.bigquery.v2.Model.LabelsEntry
  5574  	51,  // 2: google.cloud.bigquery.v2.Model.encryption_configuration:type_name -> google.cloud.bigquery.v2.EncryptionConfiguration
  5575  	0,   // 3: google.cloud.bigquery.v2.Model.model_type:type_name -> google.cloud.bigquery.v2.Model.ModelType
  5576  	31,  // 4: google.cloud.bigquery.v2.Model.training_runs:type_name -> google.cloud.bigquery.v2.Model.TrainingRun
  5577  	52,  // 5: google.cloud.bigquery.v2.Model.feature_columns:type_name -> google.cloud.bigquery.v2.StandardSqlField
  5578  	52,  // 6: google.cloud.bigquery.v2.Model.label_columns:type_name -> google.cloud.bigquery.v2.StandardSqlField
  5579  	11,  // 7: google.cloud.bigquery.v2.PatchModelRequest.model:type_name -> google.cloud.bigquery.v2.Model
  5580  	53,  // 8: google.cloud.bigquery.v2.ListModelsRequest.max_results:type_name -> google.protobuf.UInt32Value
  5581  	11,  // 9: google.cloud.bigquery.v2.ListModelsResponse.models:type_name -> google.cloud.bigquery.v2.Model
  5582  	54,  // 10: google.cloud.bigquery.v2.Model.RegressionMetrics.mean_absolute_error:type_name -> google.protobuf.DoubleValue
  5583  	54,  // 11: google.cloud.bigquery.v2.Model.RegressionMetrics.mean_squared_error:type_name -> google.protobuf.DoubleValue
  5584  	54,  // 12: google.cloud.bigquery.v2.Model.RegressionMetrics.mean_squared_log_error:type_name -> google.protobuf.DoubleValue
  5585  	54,  // 13: google.cloud.bigquery.v2.Model.RegressionMetrics.median_absolute_error:type_name -> google.protobuf.DoubleValue
  5586  	54,  // 14: google.cloud.bigquery.v2.Model.RegressionMetrics.r_squared:type_name -> google.protobuf.DoubleValue
  5587  	54,  // 15: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.precision:type_name -> google.protobuf.DoubleValue
  5588  	54,  // 16: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.recall:type_name -> google.protobuf.DoubleValue
  5589  	54,  // 17: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.accuracy:type_name -> google.protobuf.DoubleValue
  5590  	54,  // 18: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.threshold:type_name -> google.protobuf.DoubleValue
  5591  	54,  // 19: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.f1_score:type_name -> google.protobuf.DoubleValue
  5592  	54,  // 20: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.log_loss:type_name -> google.protobuf.DoubleValue
  5593  	54,  // 21: google.cloud.bigquery.v2.Model.AggregateClassificationMetrics.roc_auc:type_name -> google.protobuf.DoubleValue
  5594  	20,  // 22: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.aggregate_classification_metrics:type_name -> google.cloud.bigquery.v2.Model.AggregateClassificationMetrics
  5595  	33,  // 23: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.binary_confusion_matrix_list:type_name -> google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix
  5596  	20,  // 24: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.aggregate_classification_metrics:type_name -> google.cloud.bigquery.v2.Model.AggregateClassificationMetrics
  5597  	34,  // 25: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.confusion_matrix_list:type_name -> google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix
  5598  	54,  // 26: google.cloud.bigquery.v2.Model.ClusteringMetrics.davies_bouldin_index:type_name -> google.protobuf.DoubleValue
  5599  	54,  // 27: google.cloud.bigquery.v2.Model.ClusteringMetrics.mean_squared_distance:type_name -> google.protobuf.DoubleValue
  5600  	37,  // 28: google.cloud.bigquery.v2.Model.ClusteringMetrics.clusters:type_name -> google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster
  5601  	54,  // 29: google.cloud.bigquery.v2.Model.RankingMetrics.mean_average_precision:type_name -> google.protobuf.DoubleValue
  5602  	54,  // 30: google.cloud.bigquery.v2.Model.RankingMetrics.mean_squared_error:type_name -> google.protobuf.DoubleValue
  5603  	54,  // 31: google.cloud.bigquery.v2.Model.RankingMetrics.normalized_discounted_cumulative_gain:type_name -> google.protobuf.DoubleValue
  5604  	54,  // 32: google.cloud.bigquery.v2.Model.RankingMetrics.average_rank:type_name -> google.protobuf.DoubleValue
  5605  	28,  // 33: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.non_seasonal_order:type_name -> google.cloud.bigquery.v2.Model.ArimaOrder
  5606  	29,  // 34: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.arima_fitting_metrics:type_name -> google.cloud.bigquery.v2.Model.ArimaFittingMetrics
  5607  	9,   // 35: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.seasonal_periods:type_name -> google.cloud.bigquery.v2.Model.SeasonalPeriod.SeasonalPeriodType
  5608  	41,  // 36: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.arima_single_model_forecasting_metrics:type_name -> google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics
  5609  	19,  // 37: google.cloud.bigquery.v2.Model.EvaluationMetrics.regression_metrics:type_name -> google.cloud.bigquery.v2.Model.RegressionMetrics
  5610  	21,  // 38: google.cloud.bigquery.v2.Model.EvaluationMetrics.binary_classification_metrics:type_name -> google.cloud.bigquery.v2.Model.BinaryClassificationMetrics
  5611  	22,  // 39: google.cloud.bigquery.v2.Model.EvaluationMetrics.multi_class_classification_metrics:type_name -> google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics
  5612  	23,  // 40: google.cloud.bigquery.v2.Model.EvaluationMetrics.clustering_metrics:type_name -> google.cloud.bigquery.v2.Model.ClusteringMetrics
  5613  	24,  // 41: google.cloud.bigquery.v2.Model.EvaluationMetrics.ranking_metrics:type_name -> google.cloud.bigquery.v2.Model.RankingMetrics
  5614  	25,  // 42: google.cloud.bigquery.v2.Model.EvaluationMetrics.arima_forecasting_metrics:type_name -> google.cloud.bigquery.v2.Model.ArimaForecastingMetrics
  5615  	55,  // 43: google.cloud.bigquery.v2.Model.DataSplitResult.training_table:type_name -> google.cloud.bigquery.v2.TableReference
  5616  	55,  // 44: google.cloud.bigquery.v2.Model.DataSplitResult.evaluation_table:type_name -> google.cloud.bigquery.v2.TableReference
  5617  	42,  // 45: google.cloud.bigquery.v2.Model.GlobalExplanation.explanations:type_name -> google.cloud.bigquery.v2.Model.GlobalExplanation.Explanation
  5618  	43,  // 46: google.cloud.bigquery.v2.Model.TrainingRun.training_options:type_name -> google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions
  5619  	56,  // 47: google.cloud.bigquery.v2.Model.TrainingRun.start_time:type_name -> google.protobuf.Timestamp
  5620  	44,  // 48: google.cloud.bigquery.v2.Model.TrainingRun.results:type_name -> google.cloud.bigquery.v2.Model.TrainingRun.IterationResult
  5621  	26,  // 49: google.cloud.bigquery.v2.Model.TrainingRun.evaluation_metrics:type_name -> google.cloud.bigquery.v2.Model.EvaluationMetrics
  5622  	27,  // 50: google.cloud.bigquery.v2.Model.TrainingRun.data_split_result:type_name -> google.cloud.bigquery.v2.Model.DataSplitResult
  5623  	30,  // 51: google.cloud.bigquery.v2.Model.TrainingRun.global_explanations:type_name -> google.cloud.bigquery.v2.Model.GlobalExplanation
  5624  	54,  // 52: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.positive_class_threshold:type_name -> google.protobuf.DoubleValue
  5625  	57,  // 53: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.true_positives:type_name -> google.protobuf.Int64Value
  5626  	57,  // 54: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.false_positives:type_name -> google.protobuf.Int64Value
  5627  	57,  // 55: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.true_negatives:type_name -> google.protobuf.Int64Value
  5628  	57,  // 56: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.false_negatives:type_name -> google.protobuf.Int64Value
  5629  	54,  // 57: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.precision:type_name -> google.protobuf.DoubleValue
  5630  	54,  // 58: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.recall:type_name -> google.protobuf.DoubleValue
  5631  	54,  // 59: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.f1_score:type_name -> google.protobuf.DoubleValue
  5632  	54,  // 60: google.cloud.bigquery.v2.Model.BinaryClassificationMetrics.BinaryConfusionMatrix.accuracy:type_name -> google.protobuf.DoubleValue
  5633  	54,  // 61: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.confidence_threshold:type_name -> google.protobuf.DoubleValue
  5634  	36,  // 62: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.rows:type_name -> google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row
  5635  	57,  // 63: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry.item_count:type_name -> google.protobuf.Int64Value
  5636  	35,  // 64: google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Row.entries:type_name -> google.cloud.bigquery.v2.Model.MultiClassClassificationMetrics.ConfusionMatrix.Entry
  5637  	38,  // 65: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.feature_values:type_name -> google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue
  5638  	57,  // 66: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.count:type_name -> google.protobuf.Int64Value
  5639  	54,  // 67: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.numerical_value:type_name -> google.protobuf.DoubleValue
  5640  	39,  // 68: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.categorical_value:type_name -> google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue
  5641  	40,  // 69: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.category_counts:type_name -> google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount
  5642  	57,  // 70: google.cloud.bigquery.v2.Model.ClusteringMetrics.Cluster.FeatureValue.CategoricalValue.CategoryCount.count:type_name -> google.protobuf.Int64Value
  5643  	28,  // 71: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics.non_seasonal_order:type_name -> google.cloud.bigquery.v2.Model.ArimaOrder
  5644  	29,  // 72: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics.arima_fitting_metrics:type_name -> google.cloud.bigquery.v2.Model.ArimaFittingMetrics
  5645  	9,   // 73: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics.seasonal_periods:type_name -> google.cloud.bigquery.v2.Model.SeasonalPeriod.SeasonalPeriodType
  5646  	58,  // 74: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics.has_holiday_effect:type_name -> google.protobuf.BoolValue
  5647  	58,  // 75: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics.has_spikes_and_dips:type_name -> google.protobuf.BoolValue
  5648  	58,  // 76: google.cloud.bigquery.v2.Model.ArimaForecastingMetrics.ArimaSingleModelForecastingMetrics.has_step_changes:type_name -> google.protobuf.BoolValue
  5649  	54,  // 77: google.cloud.bigquery.v2.Model.GlobalExplanation.Explanation.attribution:type_name -> google.protobuf.DoubleValue
  5650  	1,   // 78: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.loss_type:type_name -> google.cloud.bigquery.v2.Model.LossType
  5651  	54,  // 79: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.l1_regularization:type_name -> google.protobuf.DoubleValue
  5652  	54,  // 80: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.l2_regularization:type_name -> google.protobuf.DoubleValue
  5653  	54,  // 81: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.min_relative_progress:type_name -> google.protobuf.DoubleValue
  5654  	58,  // 82: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.warm_start:type_name -> google.protobuf.BoolValue
  5655  	58,  // 83: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.early_stop:type_name -> google.protobuf.BoolValue
  5656  	3,   // 84: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.data_split_method:type_name -> google.cloud.bigquery.v2.Model.DataSplitMethod
  5657  	6,   // 85: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.learn_rate_strategy:type_name -> google.cloud.bigquery.v2.Model.LearnRateStrategy
  5658  	45,  // 86: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.label_class_weights:type_name -> google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.LabelClassWeightsEntry
  5659  	2,   // 87: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.distance_type:type_name -> google.cloud.bigquery.v2.Model.DistanceType
  5660  	7,   // 88: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.optimization_strategy:type_name -> google.cloud.bigquery.v2.Model.OptimizationStrategy
  5661  	54,  // 89: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.dropout:type_name -> google.protobuf.DoubleValue
  5662  	54,  // 90: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.min_split_loss:type_name -> google.protobuf.DoubleValue
  5663  	8,   // 91: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.feedback_type:type_name -> google.cloud.bigquery.v2.Model.FeedbackType
  5664  	54,  // 92: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.wals_alpha:type_name -> google.protobuf.DoubleValue
  5665  	10,  // 93: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.kmeans_initialization_method:type_name -> google.cloud.bigquery.v2.Model.KmeansEnums.KmeansInitializationMethod
  5666  	28,  // 94: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.non_seasonal_order:type_name -> google.cloud.bigquery.v2.Model.ArimaOrder
  5667  	4,   // 95: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.data_frequency:type_name -> google.cloud.bigquery.v2.Model.DataFrequency
  5668  	5,   // 96: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.holiday_region:type_name -> google.cloud.bigquery.v2.Model.HolidayRegion
  5669  	58,  // 97: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.decompose_time_series:type_name -> google.protobuf.BoolValue
  5670  	58,  // 98: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.clean_spikes_and_dips:type_name -> google.protobuf.BoolValue
  5671  	58,  // 99: google.cloud.bigquery.v2.Model.TrainingRun.TrainingOptions.adjust_step_changes:type_name -> google.protobuf.BoolValue
  5672  	59,  // 100: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.index:type_name -> google.protobuf.Int32Value
  5673  	57,  // 101: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.duration_ms:type_name -> google.protobuf.Int64Value
  5674  	54,  // 102: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.training_loss:type_name -> google.protobuf.DoubleValue
  5675  	54,  // 103: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.eval_loss:type_name -> google.protobuf.DoubleValue
  5676  	46,  // 104: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.cluster_infos:type_name -> google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo
  5677  	47,  // 105: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.arima_result:type_name -> google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult
  5678  	54,  // 106: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo.cluster_radius:type_name -> google.protobuf.DoubleValue
  5679  	57,  // 107: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ClusterInfo.cluster_size:type_name -> google.protobuf.Int64Value
  5680  	49,  // 108: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.arima_model_info:type_name -> google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo
  5681  	9,   // 109: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.seasonal_periods:type_name -> google.cloud.bigquery.v2.Model.SeasonalPeriod.SeasonalPeriodType
  5682  	28,  // 110: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo.non_seasonal_order:type_name -> google.cloud.bigquery.v2.Model.ArimaOrder
  5683  	48,  // 111: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo.arima_coefficients:type_name -> google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaCoefficients
  5684  	29,  // 112: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo.arima_fitting_metrics:type_name -> google.cloud.bigquery.v2.Model.ArimaFittingMetrics
  5685  	9,   // 113: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo.seasonal_periods:type_name -> google.cloud.bigquery.v2.Model.SeasonalPeriod.SeasonalPeriodType
  5686  	58,  // 114: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo.has_holiday_effect:type_name -> google.protobuf.BoolValue
  5687  	58,  // 115: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo.has_spikes_and_dips:type_name -> google.protobuf.BoolValue
  5688  	58,  // 116: google.cloud.bigquery.v2.Model.TrainingRun.IterationResult.ArimaResult.ArimaModelInfo.has_step_changes:type_name -> google.protobuf.BoolValue
  5689  	12,  // 117: google.cloud.bigquery.v2.ModelService.GetModel:input_type -> google.cloud.bigquery.v2.GetModelRequest
  5690  	15,  // 118: google.cloud.bigquery.v2.ModelService.ListModels:input_type -> google.cloud.bigquery.v2.ListModelsRequest
  5691  	13,  // 119: google.cloud.bigquery.v2.ModelService.PatchModel:input_type -> google.cloud.bigquery.v2.PatchModelRequest
  5692  	14,  // 120: google.cloud.bigquery.v2.ModelService.DeleteModel:input_type -> google.cloud.bigquery.v2.DeleteModelRequest
  5693  	11,  // 121: google.cloud.bigquery.v2.ModelService.GetModel:output_type -> google.cloud.bigquery.v2.Model
  5694  	16,  // 122: google.cloud.bigquery.v2.ModelService.ListModels:output_type -> google.cloud.bigquery.v2.ListModelsResponse
  5695  	11,  // 123: google.cloud.bigquery.v2.ModelService.PatchModel:output_type -> google.cloud.bigquery.v2.Model
  5696  	60,  // 124: google.cloud.bigquery.v2.ModelService.DeleteModel:output_type -> google.protobuf.Empty
  5697  	121, // [121:125] is the sub-list for method output_type
  5698  	117, // [117:121] is the sub-list for method input_type
  5699  	117, // [117:117] is the sub-list for extension type_name
  5700  	117, // [117:117] is the sub-list for extension extendee
  5701  	0,   // [0:117] is the sub-list for field type_name
  5702  }
  5703  
  5704  func init() { file_google_cloud_bigquery_v2_model_proto_init() }
  5705  func file_google_cloud_bigquery_v2_model_proto_init() {
  5706  	if File_google_cloud_bigquery_v2_model_proto != nil {
  5707  		return
  5708  	}
  5709  	file_google_cloud_bigquery_v2_encryption_config_proto_init()
  5710  	file_google_cloud_bigquery_v2_model_reference_proto_init()
  5711  	file_google_cloud_bigquery_v2_standard_sql_proto_init()
  5712  	file_google_cloud_bigquery_v2_table_reference_proto_init()
  5713  	if !protoimpl.UnsafeEnabled {
  5714  		file_google_cloud_bigquery_v2_model_proto_msgTypes[0].Exporter = func(v interface{}, i int) interface{} {
  5715  			switch v := v.(*Model); i {
  5716  			case 0:
  5717  				return &v.state
  5718  			case 1:
  5719  				return &v.sizeCache
  5720  			case 2:
  5721  				return &v.unknownFields
  5722  			default:
  5723  				return nil
  5724  			}
  5725  		}
  5726  		file_google_cloud_bigquery_v2_model_proto_msgTypes[1].Exporter = func(v interface{}, i int) interface{} {
  5727  			switch v := v.(*GetModelRequest); i {
  5728  			case 0:
  5729  				return &v.state
  5730  			case 1:
  5731  				return &v.sizeCache
  5732  			case 2:
  5733  				return &v.unknownFields
  5734  			default:
  5735  				return nil
  5736  			}
  5737  		}
  5738  		file_google_cloud_bigquery_v2_model_proto_msgTypes[2].Exporter = func(v interface{}, i int) interface{} {
  5739  			switch v := v.(*PatchModelRequest); i {
  5740  			case 0:
  5741  				return &v.state
  5742  			case 1:
  5743  				return &v.sizeCache
  5744  			case 2:
  5745  				return &v.unknownFields
  5746  			default:
  5747  				return nil
  5748  			}
  5749  		}
  5750  		file_google_cloud_bigquery_v2_model_proto_msgTypes[3].Exporter = func(v interface{}, i int) interface{} {
  5751  			switch v := v.(*DeleteModelRequest); i {
  5752  			case 0:
  5753  				return &v.state
  5754  			case 1:
  5755  				return &v.sizeCache
  5756  			case 2:
  5757  				return &v.unknownFields
  5758  			default:
  5759  				return nil
  5760  			}
  5761  		}
  5762  		file_google_cloud_bigquery_v2_model_proto_msgTypes[4].Exporter = func(v interface{}, i int) interface{} {
  5763  			switch v := v.(*ListModelsRequest); i {
  5764  			case 0:
  5765  				return &v.state
  5766  			case 1:
  5767  				return &v.sizeCache
  5768  			case 2:
  5769  				return &v.unknownFields
  5770  			default:
  5771  				return nil
  5772  			}
  5773  		}
  5774  		file_google_cloud_bigquery_v2_model_proto_msgTypes[5].Exporter = func(v interface{}, i int) interface{} {
  5775  			switch v := v.(*ListModelsResponse); i {
  5776  			case 0:
  5777  				return &v.state
  5778  			case 1:
  5779  				return &v.sizeCache
  5780  			case 2:
  5781  				return &v.unknownFields
  5782  			default:
  5783  				return nil
  5784  			}
  5785  		}
  5786  		file_google_cloud_bigquery_v2_model_proto_msgTypes[6].Exporter = func(v interface{}, i int) interface{} {
  5787  			switch v := v.(*Model_SeasonalPeriod); i {
  5788  			case 0:
  5789  				return &v.state
  5790  			case 1:
  5791  				return &v.sizeCache
  5792  			case 2:
  5793  				return &v.unknownFields
  5794  			default:
  5795  				return nil
  5796  			}
  5797  		}
  5798  		file_google_cloud_bigquery_v2_model_proto_msgTypes[7].Exporter = func(v interface{}, i int) interface{} {
  5799  			switch v := v.(*Model_KmeansEnums); i {
  5800  			case 0:
  5801  				return &v.state
  5802  			case 1:
  5803  				return &v.sizeCache
  5804  			case 2:
  5805  				return &v.unknownFields
  5806  			default:
  5807  				return nil
  5808  			}
  5809  		}
  5810  		file_google_cloud_bigquery_v2_model_proto_msgTypes[8].Exporter = func(v interface{}, i int) interface{} {
  5811  			switch v := v.(*Model_RegressionMetrics); i {
  5812  			case 0:
  5813  				return &v.state
  5814  			case 1:
  5815  				return &v.sizeCache
  5816  			case 2:
  5817  				return &v.unknownFields
  5818  			default:
  5819  				return nil
  5820  			}
  5821  		}
  5822  		file_google_cloud_bigquery_v2_model_proto_msgTypes[9].Exporter = func(v interface{}, i int) interface{} {
  5823  			switch v := v.(*Model_AggregateClassificationMetrics); i {
  5824  			case 0:
  5825  				return &v.state
  5826  			case 1:
  5827  				return &v.sizeCache
  5828  			case 2:
  5829  				return &v.unknownFields
  5830  			default:
  5831  				return nil
  5832  			}
  5833  		}
  5834  		file_google_cloud_bigquery_v2_model_proto_msgTypes[10].Exporter = func(v interface{}, i int) interface{} {
  5835  			switch v := v.(*Model_BinaryClassificationMetrics); i {
  5836  			case 0:
  5837  				return &v.state
  5838  			case 1:
  5839  				return &v.sizeCache
  5840  			case 2:
  5841  				return &v.unknownFields
  5842  			default:
  5843  				return nil
  5844  			}
  5845  		}
  5846  		file_google_cloud_bigquery_v2_model_proto_msgTypes[11].Exporter = func(v interface{}, i int) interface{} {
  5847  			switch v := v.(*Model_MultiClassClassificationMetrics); i {
  5848  			case 0:
  5849  				return &v.state
  5850  			case 1:
  5851  				return &v.sizeCache
  5852  			case 2:
  5853  				return &v.unknownFields
  5854  			default:
  5855  				return nil
  5856  			}
  5857  		}
  5858  		file_google_cloud_bigquery_v2_model_proto_msgTypes[12].Exporter = func(v interface{}, i int) interface{} {
  5859  			switch v := v.(*Model_ClusteringMetrics); i {
  5860  			case 0:
  5861  				return &v.state
  5862  			case 1:
  5863  				return &v.sizeCache
  5864  			case 2:
  5865  				return &v.unknownFields
  5866  			default:
  5867  				return nil
  5868  			}
  5869  		}
  5870  		file_google_cloud_bigquery_v2_model_proto_msgTypes[13].Exporter = func(v interface{}, i int) interface{} {
  5871  			switch v := v.(*Model_RankingMetrics); i {
  5872  			case 0:
  5873  				return &v.state
  5874  			case 1:
  5875  				return &v.sizeCache
  5876  			case 2:
  5877  				return &v.unknownFields
  5878  			default:
  5879  				return nil
  5880  			}
  5881  		}
  5882  		file_google_cloud_bigquery_v2_model_proto_msgTypes[14].Exporter = func(v interface{}, i int) interface{} {
  5883  			switch v := v.(*Model_ArimaForecastingMetrics); i {
  5884  			case 0:
  5885  				return &v.state
  5886  			case 1:
  5887  				return &v.sizeCache
  5888  			case 2:
  5889  				return &v.unknownFields
  5890  			default:
  5891  				return nil
  5892  			}
  5893  		}
  5894  		file_google_cloud_bigquery_v2_model_proto_msgTypes[15].Exporter = func(v interface{}, i int) interface{} {
  5895  			switch v := v.(*Model_EvaluationMetrics); i {
  5896  			case 0:
  5897  				return &v.state
  5898  			case 1:
  5899  				return &v.sizeCache
  5900  			case 2:
  5901  				return &v.unknownFields
  5902  			default:
  5903  				return nil
  5904  			}
  5905  		}
  5906  		file_google_cloud_bigquery_v2_model_proto_msgTypes[16].Exporter = func(v interface{}, i int) interface{} {
  5907  			switch v := v.(*Model_DataSplitResult); i {
  5908  			case 0:
  5909  				return &v.state
  5910  			case 1:
  5911  				return &v.sizeCache
  5912  			case 2:
  5913  				return &v.unknownFields
  5914  			default:
  5915  				return nil
  5916  			}
  5917  		}
  5918  		file_google_cloud_bigquery_v2_model_proto_msgTypes[17].Exporter = func(v interface{}, i int) interface{} {
  5919  			switch v := v.(*Model_ArimaOrder); i {
  5920  			case 0:
  5921  				return &v.state
  5922  			case 1:
  5923  				return &v.sizeCache
  5924  			case 2:
  5925  				return &v.unknownFields
  5926  			default:
  5927  				return nil
  5928  			}
  5929  		}
  5930  		file_google_cloud_bigquery_v2_model_proto_msgTypes[18].Exporter = func(v interface{}, i int) interface{} {
  5931  			switch v := v.(*Model_ArimaFittingMetrics); i {
  5932  			case 0:
  5933  				return &v.state
  5934  			case 1:
  5935  				return &v.sizeCache
  5936  			case 2:
  5937  				return &v.unknownFields
  5938  			default:
  5939  				return nil
  5940  			}
  5941  		}
  5942  		file_google_cloud_bigquery_v2_model_proto_msgTypes[19].Exporter = func(v interface{}, i int) interface{} {
  5943  			switch v := v.(*Model_GlobalExplanation); i {
  5944  			case 0:
  5945  				return &v.state
  5946  			case 1:
  5947  				return &v.sizeCache
  5948  			case 2:
  5949  				return &v.unknownFields
  5950  			default:
  5951  				return nil
  5952  			}
  5953  		}
  5954  		file_google_cloud_bigquery_v2_model_proto_msgTypes[20].Exporter = func(v interface{}, i int) interface{} {
  5955  			switch v := v.(*Model_TrainingRun); i {
  5956  			case 0:
  5957  				return &v.state
  5958  			case 1:
  5959  				return &v.sizeCache
  5960  			case 2:
  5961  				return &v.unknownFields
  5962  			default:
  5963  				return nil
  5964  			}
  5965  		}
  5966  		file_google_cloud_bigquery_v2_model_proto_msgTypes[22].Exporter = func(v interface{}, i int) interface{} {
  5967  			switch v := v.(*Model_BinaryClassificationMetrics_BinaryConfusionMatrix); i {
  5968  			case 0:
  5969  				return &v.state
  5970  			case 1:
  5971  				return &v.sizeCache
  5972  			case 2:
  5973  				return &v.unknownFields
  5974  			default:
  5975  				return nil
  5976  			}
  5977  		}
  5978  		file_google_cloud_bigquery_v2_model_proto_msgTypes[23].Exporter = func(v interface{}, i int) interface{} {
  5979  			switch v := v.(*Model_MultiClassClassificationMetrics_ConfusionMatrix); i {
  5980  			case 0:
  5981  				return &v.state
  5982  			case 1:
  5983  				return &v.sizeCache
  5984  			case 2:
  5985  				return &v.unknownFields
  5986  			default:
  5987  				return nil
  5988  			}
  5989  		}
  5990  		file_google_cloud_bigquery_v2_model_proto_msgTypes[24].Exporter = func(v interface{}, i int) interface{} {
  5991  			switch v := v.(*Model_MultiClassClassificationMetrics_ConfusionMatrix_Entry); i {
  5992  			case 0:
  5993  				return &v.state
  5994  			case 1:
  5995  				return &v.sizeCache
  5996  			case 2:
  5997  				return &v.unknownFields
  5998  			default:
  5999  				return nil
  6000  			}
  6001  		}
  6002  		file_google_cloud_bigquery_v2_model_proto_msgTypes[25].Exporter = func(v interface{}, i int) interface{} {
  6003  			switch v := v.(*Model_MultiClassClassificationMetrics_ConfusionMatrix_Row); i {
  6004  			case 0:
  6005  				return &v.state
  6006  			case 1:
  6007  				return &v.sizeCache
  6008  			case 2:
  6009  				return &v.unknownFields
  6010  			default:
  6011  				return nil
  6012  			}
  6013  		}
  6014  		file_google_cloud_bigquery_v2_model_proto_msgTypes[26].Exporter = func(v interface{}, i int) interface{} {
  6015  			switch v := v.(*Model_ClusteringMetrics_Cluster); i {
  6016  			case 0:
  6017  				return &v.state
  6018  			case 1:
  6019  				return &v.sizeCache
  6020  			case 2:
  6021  				return &v.unknownFields
  6022  			default:
  6023  				return nil
  6024  			}
  6025  		}
  6026  		file_google_cloud_bigquery_v2_model_proto_msgTypes[27].Exporter = func(v interface{}, i int) interface{} {
  6027  			switch v := v.(*Model_ClusteringMetrics_Cluster_FeatureValue); i {
  6028  			case 0:
  6029  				return &v.state
  6030  			case 1:
  6031  				return &v.sizeCache
  6032  			case 2:
  6033  				return &v.unknownFields
  6034  			default:
  6035  				return nil
  6036  			}
  6037  		}
  6038  		file_google_cloud_bigquery_v2_model_proto_msgTypes[28].Exporter = func(v interface{}, i int) interface{} {
  6039  			switch v := v.(*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue); i {
  6040  			case 0:
  6041  				return &v.state
  6042  			case 1:
  6043  				return &v.sizeCache
  6044  			case 2:
  6045  				return &v.unknownFields
  6046  			default:
  6047  				return nil
  6048  			}
  6049  		}
  6050  		file_google_cloud_bigquery_v2_model_proto_msgTypes[29].Exporter = func(v interface{}, i int) interface{} {
  6051  			switch v := v.(*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_CategoryCount); i {
  6052  			case 0:
  6053  				return &v.state
  6054  			case 1:
  6055  				return &v.sizeCache
  6056  			case 2:
  6057  				return &v.unknownFields
  6058  			default:
  6059  				return nil
  6060  			}
  6061  		}
  6062  		file_google_cloud_bigquery_v2_model_proto_msgTypes[30].Exporter = func(v interface{}, i int) interface{} {
  6063  			switch v := v.(*Model_ArimaForecastingMetrics_ArimaSingleModelForecastingMetrics); i {
  6064  			case 0:
  6065  				return &v.state
  6066  			case 1:
  6067  				return &v.sizeCache
  6068  			case 2:
  6069  				return &v.unknownFields
  6070  			default:
  6071  				return nil
  6072  			}
  6073  		}
  6074  		file_google_cloud_bigquery_v2_model_proto_msgTypes[31].Exporter = func(v interface{}, i int) interface{} {
  6075  			switch v := v.(*Model_GlobalExplanation_Explanation); i {
  6076  			case 0:
  6077  				return &v.state
  6078  			case 1:
  6079  				return &v.sizeCache
  6080  			case 2:
  6081  				return &v.unknownFields
  6082  			default:
  6083  				return nil
  6084  			}
  6085  		}
  6086  		file_google_cloud_bigquery_v2_model_proto_msgTypes[32].Exporter = func(v interface{}, i int) interface{} {
  6087  			switch v := v.(*Model_TrainingRun_TrainingOptions); i {
  6088  			case 0:
  6089  				return &v.state
  6090  			case 1:
  6091  				return &v.sizeCache
  6092  			case 2:
  6093  				return &v.unknownFields
  6094  			default:
  6095  				return nil
  6096  			}
  6097  		}
  6098  		file_google_cloud_bigquery_v2_model_proto_msgTypes[33].Exporter = func(v interface{}, i int) interface{} {
  6099  			switch v := v.(*Model_TrainingRun_IterationResult); i {
  6100  			case 0:
  6101  				return &v.state
  6102  			case 1:
  6103  				return &v.sizeCache
  6104  			case 2:
  6105  				return &v.unknownFields
  6106  			default:
  6107  				return nil
  6108  			}
  6109  		}
  6110  		file_google_cloud_bigquery_v2_model_proto_msgTypes[35].Exporter = func(v interface{}, i int) interface{} {
  6111  			switch v := v.(*Model_TrainingRun_IterationResult_ClusterInfo); i {
  6112  			case 0:
  6113  				return &v.state
  6114  			case 1:
  6115  				return &v.sizeCache
  6116  			case 2:
  6117  				return &v.unknownFields
  6118  			default:
  6119  				return nil
  6120  			}
  6121  		}
  6122  		file_google_cloud_bigquery_v2_model_proto_msgTypes[36].Exporter = func(v interface{}, i int) interface{} {
  6123  			switch v := v.(*Model_TrainingRun_IterationResult_ArimaResult); i {
  6124  			case 0:
  6125  				return &v.state
  6126  			case 1:
  6127  				return &v.sizeCache
  6128  			case 2:
  6129  				return &v.unknownFields
  6130  			default:
  6131  				return nil
  6132  			}
  6133  		}
  6134  		file_google_cloud_bigquery_v2_model_proto_msgTypes[37].Exporter = func(v interface{}, i int) interface{} {
  6135  			switch v := v.(*Model_TrainingRun_IterationResult_ArimaResult_ArimaCoefficients); i {
  6136  			case 0:
  6137  				return &v.state
  6138  			case 1:
  6139  				return &v.sizeCache
  6140  			case 2:
  6141  				return &v.unknownFields
  6142  			default:
  6143  				return nil
  6144  			}
  6145  		}
  6146  		file_google_cloud_bigquery_v2_model_proto_msgTypes[38].Exporter = func(v interface{}, i int) interface{} {
  6147  			switch v := v.(*Model_TrainingRun_IterationResult_ArimaResult_ArimaModelInfo); i {
  6148  			case 0:
  6149  				return &v.state
  6150  			case 1:
  6151  				return &v.sizeCache
  6152  			case 2:
  6153  				return &v.unknownFields
  6154  			default:
  6155  				return nil
  6156  			}
  6157  		}
  6158  	}
  6159  	file_google_cloud_bigquery_v2_model_proto_msgTypes[15].OneofWrappers = []interface{}{
  6160  		(*Model_EvaluationMetrics_RegressionMetrics)(nil),
  6161  		(*Model_EvaluationMetrics_BinaryClassificationMetrics)(nil),
  6162  		(*Model_EvaluationMetrics_MultiClassClassificationMetrics)(nil),
  6163  		(*Model_EvaluationMetrics_ClusteringMetrics)(nil),
  6164  		(*Model_EvaluationMetrics_RankingMetrics)(nil),
  6165  		(*Model_EvaluationMetrics_ArimaForecastingMetrics)(nil),
  6166  	}
  6167  	file_google_cloud_bigquery_v2_model_proto_msgTypes[27].OneofWrappers = []interface{}{
  6168  		(*Model_ClusteringMetrics_Cluster_FeatureValue_NumericalValue)(nil),
  6169  		(*Model_ClusteringMetrics_Cluster_FeatureValue_CategoricalValue_)(nil),
  6170  	}
  6171  	type x struct{}
  6172  	out := protoimpl.TypeBuilder{
  6173  		File: protoimpl.DescBuilder{
  6174  			GoPackagePath: reflect.TypeOf(x{}).PkgPath(),
  6175  			RawDescriptor: file_google_cloud_bigquery_v2_model_proto_rawDesc,
  6176  			NumEnums:      11,
  6177  			NumMessages:   39,
  6178  			NumExtensions: 0,
  6179  			NumServices:   1,
  6180  		},
  6181  		GoTypes:           file_google_cloud_bigquery_v2_model_proto_goTypes,
  6182  		DependencyIndexes: file_google_cloud_bigquery_v2_model_proto_depIdxs,
  6183  		EnumInfos:         file_google_cloud_bigquery_v2_model_proto_enumTypes,
  6184  		MessageInfos:      file_google_cloud_bigquery_v2_model_proto_msgTypes,
  6185  	}.Build()
  6186  	File_google_cloud_bigquery_v2_model_proto = out.File
  6187  	file_google_cloud_bigquery_v2_model_proto_rawDesc = nil
  6188  	file_google_cloud_bigquery_v2_model_proto_goTypes = nil
  6189  	file_google_cloud_bigquery_v2_model_proto_depIdxs = nil
  6190  }
  6191  
  6192  // Reference imports to suppress errors if they are not otherwise used.
  6193  var _ context.Context
  6194  var _ grpc.ClientConnInterface
  6195  
  6196  // This is a compile-time assertion to ensure that this generated file
  6197  // is compatible with the grpc package it is being compiled against.
  6198  const _ = grpc.SupportPackageIsVersion6
  6199  
  6200  // ModelServiceClient is the client API for ModelService service.
  6201  //
  6202  // For semantics around ctx use and closing/ending streaming RPCs, please refer to https://godoc.org/google.golang.org/grpc#ClientConn.NewStream.
  6203  type ModelServiceClient interface {
  6204  	// Gets the specified model resource by model ID.
  6205  	GetModel(ctx context.Context, in *GetModelRequest, opts ...grpc.CallOption) (*Model, error)
  6206  	// Lists all models in the specified dataset. Requires the READER dataset
  6207  	// role. After retrieving the list of models, you can get information about a
  6208  	// particular model by calling the models.get method.
  6209  	ListModels(ctx context.Context, in *ListModelsRequest, opts ...grpc.CallOption) (*ListModelsResponse, error)
  6210  	// Patch specific fields in the specified model.
  6211  	PatchModel(ctx context.Context, in *PatchModelRequest, opts ...grpc.CallOption) (*Model, error)
  6212  	// Deletes the model specified by modelId from the dataset.
  6213  	DeleteModel(ctx context.Context, in *DeleteModelRequest, opts ...grpc.CallOption) (*emptypb.Empty, error)
  6214  }
  6215  
  6216  type modelServiceClient struct {
  6217  	cc grpc.ClientConnInterface
  6218  }
  6219  
  6220  func NewModelServiceClient(cc grpc.ClientConnInterface) ModelServiceClient {
  6221  	return &modelServiceClient{cc}
  6222  }
  6223  
  6224  func (c *modelServiceClient) GetModel(ctx context.Context, in *GetModelRequest, opts ...grpc.CallOption) (*Model, error) {
  6225  	out := new(Model)
  6226  	err := c.cc.Invoke(ctx, "/google.cloud.bigquery.v2.ModelService/GetModel", in, out, opts...)
  6227  	if err != nil {
  6228  		return nil, err
  6229  	}
  6230  	return out, nil
  6231  }
  6232  
  6233  func (c *modelServiceClient) ListModels(ctx context.Context, in *ListModelsRequest, opts ...grpc.CallOption) (*ListModelsResponse, error) {
  6234  	out := new(ListModelsResponse)
  6235  	err := c.cc.Invoke(ctx, "/google.cloud.bigquery.v2.ModelService/ListModels", in, out, opts...)
  6236  	if err != nil {
  6237  		return nil, err
  6238  	}
  6239  	return out, nil
  6240  }
  6241  
  6242  func (c *modelServiceClient) PatchModel(ctx context.Context, in *PatchModelRequest, opts ...grpc.CallOption) (*Model, error) {
  6243  	out := new(Model)
  6244  	err := c.cc.Invoke(ctx, "/google.cloud.bigquery.v2.ModelService/PatchModel", in, out, opts...)
  6245  	if err != nil {
  6246  		return nil, err
  6247  	}
  6248  	return out, nil
  6249  }
  6250  
  6251  func (c *modelServiceClient) DeleteModel(ctx context.Context, in *DeleteModelRequest, opts ...grpc.CallOption) (*emptypb.Empty, error) {
  6252  	out := new(emptypb.Empty)
  6253  	err := c.cc.Invoke(ctx, "/google.cloud.bigquery.v2.ModelService/DeleteModel", in, out, opts...)
  6254  	if err != nil {
  6255  		return nil, err
  6256  	}
  6257  	return out, nil
  6258  }
  6259  
  6260  // ModelServiceServer is the server API for ModelService service.
  6261  type ModelServiceServer interface {
  6262  	// Gets the specified model resource by model ID.
  6263  	GetModel(context.Context, *GetModelRequest) (*Model, error)
  6264  	// Lists all models in the specified dataset. Requires the READER dataset
  6265  	// role. After retrieving the list of models, you can get information about a
  6266  	// particular model by calling the models.get method.
  6267  	ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error)
  6268  	// Patch specific fields in the specified model.
  6269  	PatchModel(context.Context, *PatchModelRequest) (*Model, error)
  6270  	// Deletes the model specified by modelId from the dataset.
  6271  	DeleteModel(context.Context, *DeleteModelRequest) (*emptypb.Empty, error)
  6272  }
  6273  
  6274  // UnimplementedModelServiceServer can be embedded to have forward compatible implementations.
  6275  type UnimplementedModelServiceServer struct {
  6276  }
  6277  
  6278  func (*UnimplementedModelServiceServer) GetModel(context.Context, *GetModelRequest) (*Model, error) {
  6279  	return nil, status.Errorf(codes.Unimplemented, "method GetModel not implemented")
  6280  }
  6281  func (*UnimplementedModelServiceServer) ListModels(context.Context, *ListModelsRequest) (*ListModelsResponse, error) {
  6282  	return nil, status.Errorf(codes.Unimplemented, "method ListModels not implemented")
  6283  }
  6284  func (*UnimplementedModelServiceServer) PatchModel(context.Context, *PatchModelRequest) (*Model, error) {
  6285  	return nil, status.Errorf(codes.Unimplemented, "method PatchModel not implemented")
  6286  }
  6287  func (*UnimplementedModelServiceServer) DeleteModel(context.Context, *DeleteModelRequest) (*emptypb.Empty, error) {
  6288  	return nil, status.Errorf(codes.Unimplemented, "method DeleteModel not implemented")
  6289  }
  6290  
  6291  func RegisterModelServiceServer(s *grpc.Server, srv ModelServiceServer) {
  6292  	s.RegisterService(&_ModelService_serviceDesc, srv)
  6293  }
  6294  
  6295  func _ModelService_GetModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
  6296  	in := new(GetModelRequest)
  6297  	if err := dec(in); err != nil {
  6298  		return nil, err
  6299  	}
  6300  	if interceptor == nil {
  6301  		return srv.(ModelServiceServer).GetModel(ctx, in)
  6302  	}
  6303  	info := &grpc.UnaryServerInfo{
  6304  		Server:     srv,
  6305  		FullMethod: "/google.cloud.bigquery.v2.ModelService/GetModel",
  6306  	}
  6307  	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
  6308  		return srv.(ModelServiceServer).GetModel(ctx, req.(*GetModelRequest))
  6309  	}
  6310  	return interceptor(ctx, in, info, handler)
  6311  }
  6312  
  6313  func _ModelService_ListModels_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
  6314  	in := new(ListModelsRequest)
  6315  	if err := dec(in); err != nil {
  6316  		return nil, err
  6317  	}
  6318  	if interceptor == nil {
  6319  		return srv.(ModelServiceServer).ListModels(ctx, in)
  6320  	}
  6321  	info := &grpc.UnaryServerInfo{
  6322  		Server:     srv,
  6323  		FullMethod: "/google.cloud.bigquery.v2.ModelService/ListModels",
  6324  	}
  6325  	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
  6326  		return srv.(ModelServiceServer).ListModels(ctx, req.(*ListModelsRequest))
  6327  	}
  6328  	return interceptor(ctx, in, info, handler)
  6329  }
  6330  
  6331  func _ModelService_PatchModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
  6332  	in := new(PatchModelRequest)
  6333  	if err := dec(in); err != nil {
  6334  		return nil, err
  6335  	}
  6336  	if interceptor == nil {
  6337  		return srv.(ModelServiceServer).PatchModel(ctx, in)
  6338  	}
  6339  	info := &grpc.UnaryServerInfo{
  6340  		Server:     srv,
  6341  		FullMethod: "/google.cloud.bigquery.v2.ModelService/PatchModel",
  6342  	}
  6343  	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
  6344  		return srv.(ModelServiceServer).PatchModel(ctx, req.(*PatchModelRequest))
  6345  	}
  6346  	return interceptor(ctx, in, info, handler)
  6347  }
  6348  
  6349  func _ModelService_DeleteModel_Handler(srv interface{}, ctx context.Context, dec func(interface{}) error, interceptor grpc.UnaryServerInterceptor) (interface{}, error) {
  6350  	in := new(DeleteModelRequest)
  6351  	if err := dec(in); err != nil {
  6352  		return nil, err
  6353  	}
  6354  	if interceptor == nil {
  6355  		return srv.(ModelServiceServer).DeleteModel(ctx, in)
  6356  	}
  6357  	info := &grpc.UnaryServerInfo{
  6358  		Server:     srv,
  6359  		FullMethod: "/google.cloud.bigquery.v2.ModelService/DeleteModel",
  6360  	}
  6361  	handler := func(ctx context.Context, req interface{}) (interface{}, error) {
  6362  		return srv.(ModelServiceServer).DeleteModel(ctx, req.(*DeleteModelRequest))
  6363  	}
  6364  	return interceptor(ctx, in, info, handler)
  6365  }
  6366  
  6367  var _ModelService_serviceDesc = grpc.ServiceDesc{
  6368  	ServiceName: "google.cloud.bigquery.v2.ModelService",
  6369  	HandlerType: (*ModelServiceServer)(nil),
  6370  	Methods: []grpc.MethodDesc{
  6371  		{
  6372  			MethodName: "GetModel",
  6373  			Handler:    _ModelService_GetModel_Handler,
  6374  		},
  6375  		{
  6376  			MethodName: "ListModels",
  6377  			Handler:    _ModelService_ListModels_Handler,
  6378  		},
  6379  		{
  6380  			MethodName: "PatchModel",
  6381  			Handler:    _ModelService_PatchModel_Handler,
  6382  		},
  6383  		{
  6384  			MethodName: "DeleteModel",
  6385  			Handler:    _ModelService_DeleteModel_Handler,
  6386  		},
  6387  	},
  6388  	Streams:  []grpc.StreamDesc{},
  6389  	Metadata: "google/cloud/bigquery/v2/model.proto",
  6390  }
  6391  

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